Method and apparatus for user verification with blockchain data storage

ABSTRACT

Systems and methods for enrolling and authenticating a user in an authentication system via a camera of a computing device include capturing and storing biometric information from at least one first image and at least one second image of the user taken via the camera. Prior to use, the user answers personal questions and the answers are stored as stored answer data. Later, such as at a business, the questions are presented to the user and the user provides their personal answers via a computing device. The answers are processed and uploaded to an authentication server where a comparison occurs against the stored answer data. If a match does not occur, then the authentication/identity verification processes ends. If a match does occur, then the authentication process continues. The questions match may serve as a gate function for accessing authentication data stored in a blockchain.

BACKGROUND 1. Field of the Invention

The disclosed embodiments relate to biometric security. Morespecifically, the disclosed embodiments relate to facial recognitionauthentication systems.

2. Related Art

With the growth of personal electronic devices that may be used toaccess many different user accounts, and the increasing threat ofidentity theft and other security issues, there is a growing need forways to securely access user accounts via electronic devices. Accountholders are thus often required to have longer passwords that meetvarious criteria such as using a mixture of capital and lowercaseletters, numbers, and other symbols. With smaller electronic devices,such as smart phones, smart watches, “Internet of Things” (“IoT”)devices and the like, it may become cumbersome to attempt to type suchlong passwords into the device each time access to the account isdesired and if another individual learns the user's password then theuser can be impersonated without actually being present themselves. Insome instances, users may even decide to deactivate such cumbersomesecurity measures due to their inconvenience on their devices. Thus,users of such devices may prefer other methods of secure access to theiruser accounts.

One other such method is with biometrics. For example, an electronicdevice may have a dedicated sensor that may scan a user's fingerprint todetermine that the person requesting access to a device or an account isauthorized. However, such fingerprint systems on small electronicdevices, or are often considered unreliable and unsecure.

In addition, facial recognition is generally known and may be used in avariety of contexts. Two-dimensional facial recognition is commonly usedto tag people in images on social networks or in photo editing software.Facial recognition software, however, has not been widely implemented onits own to securely authenticate users attempting to gain access to anaccount because it not considered secure enough. For example,two-dimensional facial recognition is considered unsecure because facesmay be photographed or recorded, and then the resulting prints or videodisplays showing images of the user may be used to trick the system.Accordingly, there is a need for reliable, cost-effective, andconvenient method to authenticate users attempting to log in to, forexample, a user account.

SUMMARY

The disclosed embodiments have been developed in light of the above andaspects of the invention may include a method for enrolling andauthenticating a user in an authentication system via a user's a mobilecomputing device. The user's device includes a camera.

In one embodiment, the user may enroll in the system by providingenrollment images of the user's face. The enrollment images are taken bythe camera of the mobile device as the user moves the mobile device todifferent positions relative to the user's head. The user may thusobtain enrollment images showing the user's face from different anglesand distances. The system may also utilize one or more movement sensorsof a mobile device to determine an enrollment movement path that thephone takes during the imaging. At least one image is processed todetect the user's face within the image, and to obtain biometricinformation from the user's face in the image. The image processing maybe done on the user's mobile device or at a remote device, such as anauthentication server or a user account server. The enrollmentinformation (the enrollment biometrics, movement, and other information)may be stored on the mobile device or remote device or both.

The system may then authenticate a user by the user providing at leastone authentication image via the camera of the mobile device while theuser moves the mobile device to different positions relative to theuser's head. The authentication images are processed for face detectionand facial biometric information. Path parameters may also be obtainedduring the imaging of the authentication images (authenticationmovement). The authentication information (authentication biometric,movement, and other information) is then compared with the enrollmentinformation to determine whether the user should be authenticated ordenied. Image processing and comparison may be conducted on the user'smobile device, or may be conducted remotely.

In some embodiments, multiple enrollment profiles may be created by auser to provide further security. For example, a user may create anenrollment wearing accessories such as a hat or glasses, or while makinga funny face. In further embodiments, the user's enrollment informationmay be linked to a user's email address, phone number, or other uniqueidentifier.

The authentication system may include feedback displayed on the mobiledevice to aid a user in learning and authentication with the system. Forinstance, an accuracy meter may provide feedback on a match rate of theauthentication biometrics or movement. A movement meter may providefeedback on the movement detected by the mobile device.

In some embodiments, the system may reward users who successfullyutilize the authentication system or who otherwise take fraud preventingmeasures. Such rewards may include leaderboards, status levels, rewardpoints, coupons or other offers, and the like. In some embodiments, theauthentication system may be used to login to multiple accounts.

In addition to biometric and movement matching, some embodiments mayalso utilize banding detection, glare detection, and screen edgedetection to further secure the system. In other embodiments, other userattributes may be detected and matched including users' gender, age,ethnicity, and the like.

The system may also provide gradual access to user account(s) when theuser first sets up the authentication system. As the user successfullyimplements the system, authorization may be expanded. For example,during a time period as the user gets accustomed to the authenticationsystem, lower transaction limits may be applied.

In some embodiments, the mobile device may show video feedback of whatthe user is imaging to aid the user to image his or her face duringenrollment or authentication. The video feedback may be displayed ononly a portion of the display screen of the mobile device. For example,the video feedback may be displayed in an upper portion of the displayscreen. The video feedback display may be position on a portion of thedisplay screen that corresponds with a location of a front-facing cameraof the mobile device.

To facilitate imaging in low-light, portions of the screen other thanthe video feedback may be displayed in a bright color, such as white. Insome embodiments, and LED or infrared light may be used, and nearinfrared thermal imaging may be done with an infrared camera. The mobiledevice used for imaging may thus have multiple cameras for capturevisible light and infrared images. The mobile device may also havemultiple cameras (two or more) imaging in a single spectrum or multiplespectrum to provide stereoscopic, three-dimensional images. In such anembodiment, the close-up frames (zoomed) may create the mostdifferentiation as compared to images captured from a distance. In suchan embodiment, the frames captured at a distance may be unnecessary.

In some embodiments, to provide added security, the mobile device mayoutput objects, colors, or patterns on the display screen to be detectedduring the imaging. The predetermined object or pattern may be a uniqueone-dimensional or two-dimensional barcode. For example, a QR code(two-dimensional barcode) may be displayed on the screen and reflectedoff the user's eye. If the QR code is detected in the image, then theperson may be authenticated. In other embodiments, an object may move onthe screen and the system may detect whether a user's eyes follow themovement.

In some embodiments, the system may provide prompts on a video feedbackdisplay to aid the user in moving the device relative to the user's headduring enrollment and/or authentication. The prompts may include ovalsor frames displayed on the display screen in which the user must placehis or her face by moving the mobile device until his or her face iswithin the oval or frame. The prompts may preferably be of differingsizes and may also be centered on different positions of the screen.When an actual three-dimensional person images himself or herself closeup and far away, it has been found that the biometric results aredifferent due to the barrel distortion effect of the lens at thedifferent distances. Thus, a three-dimensional person may be validatedwhen biometric results are different in the close-up and far awayimages. This also allows the user to have multiple biometric profilesfor each of the distances.

In other embodiments, biometrics from images obtained between theclose-up and far away images may be analyzed for incrementally differentbiometric results. In this manner, the morphing of the face from the farface to the warped close up face is captured and tracked. Theincremental frames during an authentication may then be matched toframes captured at similar locations during enrollment along the motionpath and compared to ensure that the expected similarities anddifference are found. This results in a motion path and captured imageand biometric data that can prove a three-dimensional person ispresently being imaged. Thus, not only are the close-up and far awaybiometrics compared, but also biometric data obtained in between. Thebiometric data obtained in between must also correspond to a correctmorphing speed along the motion path, greatly enhancing the security ofthe system.

The touch screen may be utilized in some embodiments. For example, theuser may need to enter or swipe a code or pattern in addition to theauthentication system described herein. The touchscreen may also detecta size and orientation of a user's finger, and whether a right hand or aleft hand is used on the touch screen. Voice parameters may also be usedas an added layer of security. The system may detect edge sharpness orother indicators to ensure that the obtained images are of sufficientquality for the authentication system.

When a camera has an autofocus, the autofocus may be controlled by thesystem to validate the presence of the actual, three-dimensional person.The autofocus may check that different features of the user orenvironment focus at different focal lengths. In other embodiments,authentication images may be saved to review the person who attempted toauthenticate with the system.

In some embodiments, the match thresholds required may be adapted overtime. The system may thus account for changing biometrics due to age,weight gain/loss, environment, user experience, security level, or otherfactors. In further embodiments, the system may utilize image distortionprior to obtaining biometric information to further protect againstfraudulent access.

The system may utilize any number or combination of the securityfeatures as security layers, as described herein. When authenticationfails, the system may be configured so that it is unclear which securitylayer triggered the failure to preserve the integrity of the securitysystem.

Also disclosed is a method for authenticating identity of a customer aspart of a business transaction comprising presenting a customer, withquestions, the customer questions having corresponding customer answers,and then receiving customer answers from the customer in response to thepresenting of customer questions. Next, processing the customer answersto create processed customer answers and transmitting the processedcustomer answers to a remote computing device. This method also comparesthe processed customer answers to stored data at the remote computingdevice and, responsive to the comparing determining that a match has notoccurred, denying further authentication. Responsive to the comparingdetermining that a match has occurred, allowing further authenticationby capturing and processing one or more facial images of the customer toverify the identity of the customer and liveness of the customer.

In one embodiment, the processed customer answers are encrypted, subjectto a hash operation, or both. In one embodiment, the method furthercomprises inverting the one or more facial images to capturedauthentication data and comparing the captured authentication data tostored authentication data to determining if a match occurs. In oneconfiguration, the stored authentication data is stored in a blockchainand the comparing, for a match, the reverse processed customer answersto stored customer answers data controls access to the blockchainstoring the stored authentication data.

It is also contemplated that a result of the identity and livenessverification of the customer is communicated to a business to therebyverify the identity of the customer to the business. The business may bea credit reporting agency or a lender. It is contemplated thatauthentication may further comprises verifying the liveness of thecustomer by processing a first image of the customer's face captured ata first distance from the customer and capturing a second image of thecustomer's face captured at a second distance from the customer. In oneconfiguration, the authentication further comprises comparing at leastone image of the customer's face to a previously captured image of thecustomer's face which is part of stored authentication data.

Also disclosed is an authentication system to verify a user's identitycomprising a data collection device having a processor and memorystoring non-transitory machine executable code which is executable bythe processor. The machine executable code of the data collection devicemay be configured to present user related questions to the user andreceive answers to the user related questions. The answers are enteredby the user into the data collection device. It is also configured toprocess the answers to create secured answer data, transmit the securedanswer data, and responsive to instructions from a remote server,collect and transmit collected authentication data from the user.

Also part of the system is the remote server having a processor andmemory storing non-transitory machine executable code which isexecutable by the processor, such that the machine executable code isconfigured to receive the secured answer data from the data collectiondevice and process the secured answer to determine if the receivedsecured answer data matches stored secured answer data. Responsive tothe received secured answer data not matching the stored secured answerdata, denying access to stored authentication data for the user.Responsive to the received secured answer data matching the storedsecured answer data, then initiating an authentication session bycommunicating with the data collection device to collect and transmitcollected authentication data, and then receive collected authenticationdata from the data collection device. The machine executable code isfurther configured to compare the collected authentication data receivedfrom the data collection device to stored user authentication datastored on the remote server to determine if a match occurs, such that amatch verifies the identity of the user.

In one embodiment, the secured answer data comprises encrypted answersor hashed answers. The collected authentication data may comprise one ormore images of the user captured by a camera of the data collectiondevice. The user authentication data may comprise a first image of theuser's face captured, by the camera, at a first distance separating theuser and the camera and second image of the user's face captured, by thecamera, at a second distance separating the user and the camera, suchthat the first distance is different from the second distance. In oneconfiguration, this system further comprises transmitting a verifiedidentity notice to a third party server and responsive thereto,receiving data from the third party server as part of a businesstransaction. It is also contemplated that the stored user authenticationdata is stored in a blockchain and the blockchain storing the storeduser authentication data is only accessed when the received securedanswer data matches the stored secured answer data.

An authentication system for use by a business to verify identity of auser. In one embodiment, the authentication system comprises a datacollection device having a screen and a user interface. The datacollection device is configured to receive answers from the user toquestions presented to the user, process the answers to create secureanswer data, and transmit the secure answer data to a verificationserver. Also part of this embodiment is a verification server configuredto receive the secure answer data from the data collection device andcompare the secure answer data, or processed secure answer data, tostored answer data. Responsive to the comparing determining that thesecure answer data or processed secure answer data does not match thestored answer data, terminating the identify verification. Responsive tothe comparing determining the secure answer data or processed secureanswer data matchings the stored answer data, then initiating anauthentication session which includes capture of one or more images ofthe customer's face with a camera associated with the data collectiondevice or another device.

The data collection device may be an electronic device owned by theuser. The data collection device may be an electronic device owned bythe business. In one embodiment, the stored answer data is created byperforming the same processing on the answers as occurred by the datacollection device to form the secure answer data. In one configuration,the questions presented to the user are based on information personal tothe user.

In one embodiment, the step of initiating an authentication sessioncomprises providing notice, from the verification server, to initiatethe authentication session by sending a message from the verificationserver to the data collection device or the another device, and then,capturing at least one image of the user with a camera associated withthe data collection device or the another device. This step alsoincludes processing the at least one image to generate captured imagedata and transmitting the captured image data to the verificationserver. At the verification server, processing the captured image datato verify three dimensionality of the user and comparing the capturedimage data to stored image data derived from at least one previouslycaptured image of the user to determine if match occurs within athreshold range. Then, responsive to verifying three dimensionality ofthe user and obtaining the match within the threshold range, thenverifying the identity of the user to the business. The system of claim15 wherein the stored authentication data, such as biometric data, isstored in a blockchain. In one embodiment, the one or more images of theuser's face comprises a first image captured with the camera at a firstdistance from the user and a second image captured with the camera at asecond distance from the user, the first distance different than thesecond distance.

Also disclosed is a method for verifying identity of a customer by abusiness comprising initiating an identity verification session for thecustomer. At the business, presenting questions to the customer whichhave stored answers that are stored at a remote location and also at thebusiness, receiving customer answers to the questions. Then,transmitting the customer answers or a processed version of the customeranswers to an authentication system. At the authentication system, whichmay be remote from the user, receiving the customer answers or theprocessed version of the customer answers at the authentication system.The authentication system compares the customer answers or the processedversion of the customer answers to stored customer answers or a storedprocessed version of the customer answers to determine if a matchoccurs. If a match does not occur, providing notice to the business of afailure to match and ending the identity verification processes. If amatch does occur, initiating an authentication process by obtaining oneor more images of the customer's face with a camera and processing oneor more of the images of the customer's face to generate captured facialimage data. Then, transmitting the captured facial image data to theauthentication system, and processing the captured facial image data todetermine three-dimensionality and liveness of the customer generatingthe captured facial image data. This method of operation then comparesthe captured facial image data to stored facial image data confirm thestored facial image data matches the captured facial image data, thestored facial image data based on previously captured images of thecustomer's face.

This method of operation may further comprise, responsive to the storedfacial image data matching the captured facial image data, sending anidentity verification success message to the business, to a creditreporting agency so the credit reporting agency can sent a credit reportto the business, to a lender so the lender will provide a loan orfinancing to the customer, or any combination thereof.

The step of capturing the one or more images of the user may comprise afirst image capture with the camera a first distance from the customer'sface and a second image captured with the camera a second distance fromthe user's face such that the first distance is different than thesecond distance. The customer answers may be encrypted or hashed priorto transmitting to the authentication system. In one configuration, thestep of comparing the customer answers or the processed version of thecustomer answers to stored customer answers or a stored processedversion of the customer answers controls access to authentication datastored is a blockchain.

Other systems, methods, features and advantages of the invention will beor will become apparent to one with skill in the art upon examination ofthe following figures and detailed description. It is intended that allsuch additional systems, methods, features and advantages be includedwithin this description, be within the scope of the invention, and beprotected by the accompanying claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The components in the figures are not necessarily to scale, emphasisinstead being placed upon illustrating the principles of the invention.In the figures, like reference numerals designate corresponding partsthroughout the different views.

FIG. 1 illustrates an example environment of use of the facialrecognition authentication system, according to one exemplaryembodiment.

FIG. 2 illustrates an example embodiment of a mobile device.

FIG. 3 illustrates exemplary software modules that are part of themobile device and server.

FIG. 4 shows a method for performing facial recognition authenticationaccording to one embodiment.

FIG. 5 shows a method for enrolling a user in a facial recognitionauthentication system, according to one exemplary embodiment.

FIGS. 6A and 6B show an example of movement of a mobile device about auser's face according to one exemplary embodiment.

FIGS. 7A and 7B show an example of movement of a mobile device about auser's face according to one exemplary embodiment.

FIG. 8 shows a method of providing authentication information in afacial recognition authentication system, according to one exemplaryembodiment.

FIG. 9 shows a method of verifying authentication credential in a facialrecognition authentication system, according to one exemplaryembodiment.

FIG. 10 illustrates an exemplary display showing a graphical and numericfeedback in a facial recognition authentication system.

FIGS. 11A, 11B, and 11C illustrate exemplary video feedback displayscorresponding to front-facing camera positions in a facial recognitionauthentication system.

FIG. 12 shows an exemplary video display feedback of a facialrecognition authentication system where edge pixels on the sides of thedisplay are stretched horizontally.

FIGS. 13A and 13B illustrates exemplary screen displays with facealignment indicators shown as an oval to serve as a guide as the usermoves the mobile device closer to or away from their face.

FIG. 14 illustrates an exemplary mobile device display showing agraphical code entry interface with an imaging area.

FIG. 15 illustrates an example mobile device display showing a numericand graphical code entry interface with an imaging area.

FIG. 16 shows a system for biometric identification using root identityinformation, according to an exemplary embodiment.

FIG. 17 shows a method for authenticating using a root identificationsystem, according to one exemplary embodiment.

FIG. 18 shows a method of remotely establishing a biometric identity,according to one exemplary embodiment.

FIG. 19 shows a system of biometric authentication using a blockchain,according to an exemplary embodiment.

FIG. 20 is a schematic of a computing or mobile device such as one ofthe devices described above, according to one exemplary embodiment

FIG. 21 illustrates a block diagram of an example system and environmentof use.

FIG. 22 illustrates a flow chart providing an example method ofoperation.

DETAILED DESCRIPTION OF EMBODIMENTS

A system and method for providing secure and convenient facialrecognition authentication will be described below. The system andmethod may be achieved without the need for additional expensivebiometric readers or systems while offering enhanced security overconventional facial recognition systems.

Facial Recognition Authentication Environment

FIG. 1 illustrates an example environment of use of the facialrecognition authentication system described herein. This is but onepossible environment of use and system. It is contemplated that, afterreading the specification provided below in connection with the figures,one of ordinary skill in the art may arrive at different environments ofuse and configurations.

In this environment, a user 108 may have a mobile device 112 which maybe used to access one or more of the user's accounts via authenticationsystems. A user 108 may have a mobile device 112 that can capture apicture of the user 108, such as an image of the user's face. The usermay use a camera 114 on or connected to the mobile device 112 to capturean image or multiple images or video of himself or herself. The mobiledevice 112 may comprise any type of mobile device capable of capturingan image, either still or video, and performing processing of the imageor communication over a network.

In this embodiment, the user 108 may carry and hold the mobile device112 to capture the image. The user may also wear or hold any number ofother devices. For, example, the user may wear a watch 130 containingone or more cameras 134 or biosensors disposed on the watch. The camera134 may be configured to create an image from visible light as well asinfrared light. The camera 134 may additionally or alternatively employimage intensification, active illumination, or thermal vision to obtainimages in dark environments.

When pointed towards a user 108, the camera 134 may capture an image ofthe user's face. The camera 134 may be part of a module that may eitherinclude communication capability that communicates with either a mobiledevice 112, such as via Bluetooth®, NFC, or other format, orcommunication directly with a network 116 over a wired or wireless link154. The watch 130 may include a screen on its face to allow the user toview information. If the camera module 134 communicates with the mobiledevice 112, the mobile device 134 may relay communications to thenetwork 116. The mobile device 134 may be configured with more than onefront facing camera 114 to provide for a 3D or stereoscopic view, or toobtain images across different spectral ranges, such as near infraredand visible light.

The mobile device 112 is configured to wirelessly communicate over anetwork 116 with a remote server 120. The server 120 may communicatewith one or more databases 124. The network 116 may be any type ofnetwork capable of communicating to and from the mobile device includingbut not limited to a LAN, WAN, PAN, or the Internet. The mobile device112 may communicate with the network via a wired or wireless connection,such as via Ethernet, Wi-Fi, NFC, and the like. The server 120 mayinclude any type of computing device capable of communicating with themobile device 112. The server 120 and mobile device 112 are configuredwith a processor and memory and are configured to execute machinereadable code or machine instructions stored in the memory.

The database 124, stored on mobile device or remote location as shown,may contain facial biometric information and authentication informationof users 108 to identify the users 108 to allow access to associateduser data based on one or more images or biometric information receivedfrom the mobile device 112 or watch 134. The data may be, for example,information relating to a user account or instruction to allow access toa separate account information server 120B. The term biometric data mayinclude among other information biometric information concerning facialfeatures and path parameters. Examples of path parameters may include anacceleration and speed of the mobile device, angle of the mobile deviceduring image capture, distance of the mobile device to the user, pathdirection in relation to the user's face position in relation to theuser, or any other type parameter associated with movement of the mobiledevice or the user face in relation to a camera. Other data may also beincluded such as GPS data, device identification information, and thelike.

In this embodiment, the server 120 processes requests for identificationfrom the mobile device 112 or user 108. In one configuration, the imagecaptured by the mobile device 112, using facial detection, comprises oneor more images of the user's face 108 during movement of the mobiledevice relative to the user's face, such as in a side to side orhorizontal arc or line, vertical arc or line, forward and backwards fromthe user's face, or any other direction of motion. In anotherconfiguration, the mobile device 112 calculates biometric informationfrom the obtained images, and sends the biometric information to theserver 120. In yet another embodiment, the mobile device 112 comparesbiometric information with stored biometric information on the mobiledevice 112, and sends an authentication result from the comparison tothe server 120.

The data including either the image(s), biometric information, or bothare sent over the network 116 to the server 120. Using image processingand image recognition algorithms, the server 120 processes the person'sbiometric information, such as facial data, and compares the biometricinformation with biometric data stored in the database 124 to determinethe likelihood of a match. In other embodiments, the image processingand comparison is done on the mobile device 112, and data sent to theserver indicates a result of the comparison. In further embodiments, theimage processing and comparison is done on the mobile device 112 withoutaccessing the server, for example, to obtain access to the mobile device112 itself.

By using facial recognition processing, an accurate identity match maybe established. Based on this and optionally one or more other factors,access may be granted, or an unauthorized user may be rejected. Facialrecognition processing is known in the art (or is an establishedprocess) and as a result, it is not described in detail herein.

Also shown is a second server 120B with associated second database 124B,and third server 120C with associated third database 124C. The secondand third database may be provided to contain additional informationthat is not available on the server 120 and database 124. For example,one of the additional servers may only be accessed based on theauthentication of the user 108 performed by the server 120.

Executing on the mobile device 112 is one or more software applications.This software is defined herein as an identification application (IDApp). The ID App may be configured with either or both of facialdetection and facial recognition and one or more software modules whichmonitor the path parameters and/or biometric data. Facial detection asused herein refers to a process which detects a face in an image. Facialrecognition as used herein refers to a process that can analyze a faceusing an algorithm, mapping its facial features, and converting them tobiometric data, such as numeric data. The biometric data can be comparedto that derived from one or more different images for similarities ordis-similarities. If a high percentage of similarity is found in thebiometric data, the individual shown in the images may be considered amatch.

With the ultimate goal of matching a face of a user to an identity orimage stored in a database 124, to authenticate the user, the ID App mayfirst process the image captured by the camera 114, 134 to identify andlocate the face that is in the image. As shown in FIG. 1, there may bethe face 108. The authentication may be used for logging into an onlineaccount or for numerous other access control functions.

The portion of the photo that contains the detected face may then becropped, cut, and stored for processing by one or more facialrecognition algorithms. By first detecting the face in the image andcropping only that portion of the face, the facial recognition algorithmneed not process the entire image. Further, in embodiments where thefacial recognition processing occurs remotely from the mobile device112, such as at a server 120, much less image data is required to besent over the network to the remote location. It is contemplated thatthe entire image, a cropped face, or only biometric data may be sent tothe remote server 120 for processing.

Facial detection software can detect a face from a variety of angles.However, facial recognition algorithms are most accurate in straight onimages in well-lit situations. In one embodiment, the highest qualityface image for facial recognition that is captured is processed first,then images of the face that are lower quality or at different anglesother than straight toward the face are then processed. The processingmay occur on the mobile device or at a remote server which has access tolarge databases of image data or facial identification data.

The facial detection is preferred to occur on the mobile device and isperformed by the mobile device software, such as the ID App. Thisreduces the number or size of images (data) that are sent to the serverfor processing where faces are not found and minimizes the overallamount of data that must be sent over the network. This reducesbandwidth needs and network speed requirements are reduced.

In another preferred embodiment, the facial detection, facialrecognition, and biometric comparison all occur on the mobile device.However, it is contemplated that the facial recognition processing mayoccur on the mobile device, the remote server, or both.

FIG. 2 illustrates an example embodiment of a mobile device. This is butone possible mobile device configuration and as such it is contemplatedthat one of ordinary skill in the art may differently configure themobile device. The mobile device 200 may comprise any type of mobilecommunication device capable of performing as described below. Themobile device may comprise a PDA, cellular telephone, smart phone,tablet PC, wireless electronic pad, an IoT device, a “wearable”electronic device or any other computing device.

In this example embodiment, the mobile device 200 is configured with anouter housing 204 configured to protect and contain the componentsdescribed below. Within the housing 204 is a processor 208 and a firstand second bus 212A, 212B (collectively 212). The processor 208communicates over the buses 212 with the other components of the mobiledevice 200. The processor 208 may comprise any type processor orcontroller capable of performing as described herein. The processor 208may comprise a general-purpose processor, ASIC, ARM, DSP, controller, orany other type processing device. The processor 208 and other elementsof the mobile device 200 receive power from a battery 220 or other powersource. An electrical interface 224 provides one or more electricalports to electrically interface with the mobile device, such as with asecond electronic device, computer, a medical device, or a powersupply/charging device. The interface 224 may comprise any typeelectrical interface or connector format.

One or more memories 210 are part of the mobile device 200 for storageof machine readable code for execution on the processor 208 and forstorage of data, such as image data, audio data, user data, medicaldata, location data, accelerometer data, or any other type of data. Thememory 210 may comprise RAM, ROM, flash memory, optical memory, ormicro-drive memory. The machine-readable code as described herein isnon-transitory.

As part of this embodiment, the processor 208 connects to a userinterface 216. The user interface 216 may comprise any system or deviceconfigured to accept user input to control the mobile device. The userinterface 216 may comprise one or more of the following: keyboard,roller ball, buttons, wheels, pointer key, touch pad, and touch screen.A touch screen controller 230 is also provided which interfaces throughthe bus 212 and connects to a display 228.

The display comprises any type display screen configured to displayvisual information to the user. The screen may comprise a LED, LCD, thinfilm transistor screen, OEL CSTN (color super twisted nematic), TFT(thin film transistor), TFD (thin film diode), OLED (organiclight-emitting diode), AMOLED display (active-matrix organiclight-emitting diode), capacitive touch screen, resistive touch screenor any combination of these technologies. The display 228 receivessignals from the processor 208 and these signals are translated by thedisplay into text and images as is understood in the art. The display228 may further comprise a display processor (not shown) or controllerthat interfaces with the processor 208. The touch screen controller 230may comprise a module configured to receive signals from a touch screenwhich is overlaid on the display 228.

Also part of this exemplary mobile device is a speaker 234 andmicrophone 238. The speaker 234 and microphone 238 may be controlled bythe processor 208. The microphone 238 is configured to receive andconvert audio signals to electrical signals based on processor 208control. Likewise, the processor 208 may activate the speaker 234 togenerate audio signals. These devices operate as is understood in theart and as such are not described in detail herein.

Also connected to one or more of the buses 212 is a first wirelesstransceiver 240 and a second wireless transceiver 244, each of whichconnect to respective antennas 248, 252. The first and secondtransceiver 240, 244 are configured to receive incoming signals from aremote transmitter and perform analog front-end processing on thesignals to generate analog baseband signals. The incoming signal maybefurther processed by conversion to a digital format, such as by ananalog to digital converter, for subsequent processing by the processor208. Likewise, the first and second transceiver 240, 244 are configuredto receive outgoing signals from the processor 208, or another componentof the mobile device 208, and up convert these signal from baseband toRF frequency for transmission over the respective antenna 248, 252.Although shown with a first wireless transceiver 240 and a secondwireless transceiver 244, it is contemplated that the mobile device 200may have only one such system or two or more transceivers. For example,some devices are tri-band or quad-band capable, or have Bluetooth®, NFC,or other communication capability.

It is contemplated that the mobile device, and hence the first wirelesstransceiver 240 and a second wireless transceiver 244 may be configuredto operate according to any presently existing or future developedwireless standard including, but not limited to, Bluetooth, WI-FI suchas IEEE 802.11 a,b,g,n, wireless LAN, WMAN, broadband fixed access,WiMAX, any cellular technology including CDMA, GSM, EDGE, 3G, 4G, 5G,TDMA, AMPS, FRS, GMRS, citizen band radio, VHF, AM, FM, and wirelessUSB.

Also part of the mobile device is one or more systems connected to thesecond bus 212B which also interface with the processor 208. Thesedevices include a global positioning system (GPS) module 260 withassociated antenna 262. The GPS module 260 can receive and processingsignals from satellites or other transponders to generate location dataregarding the location, direction of travel, and speed of the GPS module260. GPS is generally understood in the art and hence not described indetail herein. A gyroscope 264 connects to the bus 212B to generate andprovide orientation data regarding the orientation of the mobile device204. A magnetometer 268 is provided to provide directional informationto the mobile device 204. An accelerometer 272 connects to the bus 212Bto provide information or data regarding shocks or forces experienced bythe mobile device. In one configuration, the accelerometer 272 andgyroscope 264 generate and provide data to the processor 208 to indicatea movement path and orientation of the mobile device.

One or more cameras (still, video, or both) 276 are provided to captureimage data for storage in the memory 210 and/or for possibletransmission over a wireless or wired link or for viewing later. The oneor more cameras 276 may be configured to detect an image using visiblelight and/or near-infrared light. The cameras 276 may also be configuredto utilize image intensification, active illumination, or thermal visionto obtain images in dark environments. The processor 208 may processimage data to perform image recognition, such as in the case of, facialdetection, item detection, facial recognition, item recognition, orbar/box code reading.

A flasher and/or flashlight 280, such as an LED light, are provided andare processor controllable. The flasher or flashlight 280 may serve as astrobe or traditional flashlight. The flasher or flashlight 280 may alsobe configured to emit near-infrared light. A power management module 284interfaces with or monitors the battery 220 to manage power consumption,control battery charging, and provide supply voltages to the variousdevices which may require different power requirements.

FIG. 3 illustrates exemplary software modules that are part of themobile device and server. Other software modules may be provided toprovide the functionality described below. It is provided that for thefunctionality described herein there is matching software(non-transitory machine-readable code, machine executable instructionsor code) configured to execute the functionality. The software would bestored on a memory and executable by a processor.

In this example confirmation, the mobile device 304 includes a receivemodule 320 and a transmit module 322. These software modules areconfigured to receive and transmit data to remote device, such ascameras, glasses, servers, cellular towers, or WIFI system, such asrouter or access points.

Also part of the mobile device 304 is a location detection module 324configured to determine the location of the mobile device, such as withtriangulation or GPS. An account setting module 326 is provided toestablish, store, and allow a user to adjust account settings. A log inmodule 328 is also provided to allow a user to log in, such as withpassword protection, to the mobile device 304. A facial detection module308 is provided to execute facial detection algorithms while a facialrecognition module 321 includes software code that recognizes the faceor facial features of a user, such as to create numeric values whichrepresent one or more facial features (facial biometric information)that are unique to the user.

An information display module 314 controls the display of information tothe user of the mobile device. The display may occur on the screen ofthe mobile device or watch. A user input/output module 316 is configuredto accept data from and display data to the user. A local interface 318is configured to interface with other local devices, such as usingBluetooth® or other shorter-range communication, or wired links usingconnectors to connected cameras, batteries, data storage elements. Allthe software (with associated hardware) shown in the mobile device 304operate to provide the functionality described herein.

Also shown in FIG. 3 is the server software module 350. These modulesare located remotely from the mobile device, but can be located on anyserver or remote processing element. As is understood in the art,networks and network data use a distributed processing approach withmultiple servers and databases operating together to provide a unifiedserver. As a result, it is contemplated that the module shown in theserver block 350 may not all be located at the same server or at thesame physical location.

As shown in FIG. 3, the server 350 includes a receive module 352 and atransmit module 354. These software modules are configured to receiveand transmit data to remote devices, such as cameras, watches, glasses,servers, cellular towers, or WIFI systems, such as router or accesspoints.

An information display module 356 controls a display of information atthe server 350. A user input/output module 358 controls a user interfacein connection with the local interface module 360. Also located on theserver side of the system is a facial recognition module 366 that isconfigured to process the image data from the mobile device. The facialrecognition module 366 may process the image data to generate facialdata (biometric information) and perform a compare function in relationto other facial data to determine a facial match as part of an identifydetermination.

A database interface 368 enables communication with one or moredatabases that contain information used by the server modules. Alocation detection module 370 may utilize the location data from themobile device 304 for processing and to increase accuracy. Likewise, anaccount settings module 372 controls user accounts and may interfacewith the account settings module 326 of the mobile device 304. Asecondary server interface 374 is provided to interface and communicatewith one or more other servers.

One or more databases or database interfaces are provided to facilitatecommunication with and searching of databases. In this exampleembodiment the system includes an image database that contains images orimage data for one or more people. This database interface 362 may beused to access image data users as part of the identity match process.Also part of this embodiment is a personal data database interface 376and privacy settings data module 364. These two modules 376, 364 operateto establish privacy setting for individuals and to access a databasethat may contain privacy settings.

Authentication System

An authentication system with path parameters that is operable in theabove described environment and system will now be described as shown inFIG. 4. FIG. 4 shows a method for performing facial recognitionauthentication with path parameters according to one embodiment of theinvention. As will be described in more detail below, the systemutilizes the features of the mobile device 112 and server 120 definedabove to generate a secure and convenient login system as one example ofan authentication system. This reduces the burden of the user having totype in complex passwords onto a small screen of a mobile device,prevents fraud through means such as key logging or screen shotcaptures, and increases security by combining several path parametersand/or device parameters which must be met before user is authenticated.

In step 410, the system enrolls a user in the facial recognitionauthentication system. In one embodiment, an authentication server, suchas the server 120 (FIG. 1), may be configured to authenticate a user toallow access to a user's account, such as a bank or other account, viathe mobile device 112. The authentication server 120 may be included asa part of a server of the institution or entity providing user accounts(hereinafter “account server”), or the authentication server may beprovided separately. For example, in the environment shown in FIG. 1,Servers 120B and 120C may represent account servers. In otherembodiments, the account server and the authentication server are one inthe same. In one embodiment, the authentication server 120 may providean authentication application to the user for installation on the mobiledevice 112.

An enrollment process according to one embodiment will be described withreference to FIG. 5. In this embodiment, a user via a mobile device 112establishes a connection between the mobile device 112 and the accountserver 120B in step 510. As just one example, the user may establish aconnection with a server of a financial institution such as a bank, orthis connection may occur later in the process after authentication. Theuser then provides typical login information to authenticate the user,such as a user name and password for a financial account in step 512. Instep 514, the user may next receive a prompt at the mobile device 112 toenroll in the facial recognition authentication system. The user then,via the user interface, indicates that he or she would like to set upthe authentication system in response to the prompt.

Next, in step 516, the mobile device 112 may send device information tothe authentication server 120. The device information may include amongother information a device identifier that uniquely identifies themobile device of the user. Such information may include devicemanufacturer, model number, serial number, and mobile networkinformation. In step 518, when the authentication server 120 isincorporated with the account server 120B, the authentication server 120associates and stores the device information with the user's accountinformation. When the authentication server 120 is separate from theaccount server 120B, the account server 120B may generate a uniqueidentifier related to the account information and send the uniqueidentifier to the authentication server 120. The authentication server120 may associate the device information and the unique identifier witheach other and may store the information in a database 124.

The user is next prompted to provide a plurality of images of his or herface using a camera 114 on the mobile device 112 (hereinafter,“enrollment images”) in step 510. The enrollment images of the user'sface are taken as the user holds the mobile device and moves the mobiledevice to different positions relative to his or her head and face.Thus, the enrollment images of the user's face are taken from manydifferent angles or positions. Furthermore, the path parameters of themobile device are monitored and recorded for future comparison in step522. Some non-limiting examples of how a user might hold a mobile deviceand take a plurality of images of her face is shown in FIGS. 6A-7B.

In FIGS. 6A and 6B, the user holds the mobile device 112 on one side ofhis or her face, and moves the mobile device 112 in an arc like pathhorizontally about his or her face until the mobile device 112 is on theother side of her or her face. In FIGS. 7A and 7B, the user holds themobile device 112 far away from his or her face, and then brings themobile device 112 forward closer to his or her face. Of course, anynumber of other paths may be used in addition to those shown in FIGS.6A-7B. Additionally, the user may move his or her head while the camerais held fixed. The user could also hold the camera steady and move theirhead in relation to the camera. This method thus can be implemented witha webcam on a laptop or desktop, or on any other device, such as an IoTdevice where a camera is mounted on a similarly stationary location orobject.

The enrollment images may be obtained as follows. The user holds andorients a mobile device 112 with a camera 114 so that the camera 114 ispositioned to image the user's face. For example, the user may use afront facing camera 114 on a mobile device 112 with a display screen andmay confirm on the display screen that his or her face is in position tobe imaged by the camera 114.

Once the user has oriented the device, the device may begin obtainingthe enrollment images of the user. In one embodiment, the user may pressa button on the device 112 such as on a touchscreen or other button onthe device to initiate the obtaining of the enrollment images. The userthen moves the mobile device to different positions relative to his orher head as the device images the user's face from a plurality of anglesor positions as described above. When the above-mentioned front-facingcamera is used, the user may continually confirm that his or her face isbeing imaged by viewing the imaging on the display screen. The user mayagain press the button to indicate that the imaging is completed.Alternatively, the user may hold the button during imaging, and thenrelease the button to indicate that imaging is complete.

As described above, the mobile device 112 may include face detection. Inthis embodiment in step 524, the mobile device may detect the user'sface in each of the enrollment images, crop the images to include onlythe user's face, and send, via a network, the images to theauthentication server 120. In step 526, upon receipt of the enrollmentimages, the authentication server 120 performs facial recognition on theimages to determine biometric information (“enrollment biometrics”) forthe user. The authentication server 120 may then associate theenrollment biometrics with the device information and the uniqueidentifier (or account information) and stores the biometric informationin the database 124 in step 528. For added security, in step 530, themobile device 112 and the authentication server 120 may be configured todelete the enrollment images after the enrollment biometrics of the userare obtained.

In another embodiment, the mobile device 112 may send the images to theauthentication server 120 without performing face detection. Theauthentication server 120 may then perform the face detection, facialrecognition, and biometric information processing. In anotherembodiment, the mobile device 112 may be configured to perform thefacial detection, facial recognition, and biometric processing, and thensend the results or data resulting from the processing to theauthentication server 120 to be associated with the unique identifier oruser account. This prevents sensitive personal data (images) fromleaving the user's device. In yet another embodiment, the mobile device112 may perform each of the above-mentioned steps, and the mobile device112 may store the enrollment information without sending any of theenrollment biometrics or images to the server.

In one embodiment, the mobile device's gyroscope, magnetometer, andaccelerometer are configured to generate and store data while the usermoves the mobile device about his or her head to obtain the enrollmentimages (path parameters). The mobile device may process this data instep 532 to determine a path or arc in which the mobile device movedwhile the user imaged his or her face (“enrollment movement”). By usingdata from the accelerometer, magnetometer, and gyroscope, the system maycheck when a user is ready to begin scanning himself/herself, as well asdetermining the scan path. The data is thus used to determine when tostart and stop the scan interval. The data may additionally include thetime elapsed during scanning. This time may be measured from the userpressing the button to start and stop the imaging, or may be measuredfrom the duration the button is held down while imaging, or during moremovement or to complete sweep.

The enrollment movement of the mobile device 112 (which is data thatdefined the movement of the mobile device during image capture) may besent to the authentication server 120. The authentication server 120associates and stores the enrollment movement, the enrollmentbiometrics, the device information, and the unique identifier or accountinformation. Alternatively, the data generated by the gyroscope,magnetometer, and accelerometer may be sent to the server 120, and theserver 120 may process the data to determine the enrollment movement.

Thus, in the above described embodiment, the enrollment information maythus comprise the device information, the enrollment biometrics, and theenrollment movement (based on movement of the mobile device 112).

Returning to FIG. 4, once enrollment is complete, the authenticationserver 120 may later receive credentials from a user attempting toauthenticate with the system as shown in step 420. For example, a usermay attempt to log in to a user account. When a user attempts to log in,instead of or in addition to providing typical account credentials suchas user name and password, the user may again take a plurality of imagesor video of his or her face as the mobile device 112 is held in the handand moved to different positions relative to the head (“authenticationimages”) in the same manner as was done during enrollment (such as shownin FIGS. 6A-7B). In this manner, the user may provide the necessaryimages (the term images includes video as video is a succession ofimages) from many different angles and/or positions, and may providepath parameters of the device while obtaining the images(“authentication movement”) to both confirm the identity of the user aswell as the liveness and realness of that individual to ensure it is nota video, screen shot, or other representation of the person.

In one embodiment outlined in FIG. 8, the user via the mobile device 112obtains several authentication images in step 810 while moving themobile device 112 to different positions relative to the user's head.Using facial detection in step 812, the mobile device 112 detects theuser's face in each of the authentication images, crops the images, andsends the images to the authentication server 120. In anotherembodiment, the mobile device 112 sends the images to the server 124,and the server 124 performs facial detection. In step 814, theauthentication routing 120 may perform facial recognition on theauthentication images to obtain biometric information (“authenticationbiometrics”). In another embodiment, the mobile device 112 performsfacial recognition to obtain the authentication biometrics and sends theauthentication biometrics to the server 120.

In step 816, the mobile device 112 sends the device informationidentifying the device and sends path parameters such as gyroscope,magnetometer, and accelerometer information defining the path of themobile device taken during imaging, as well as the elapsed time duringimaging (“authentication movement”) to the server 120. The credentialsreceived by the authentication server 120 for a login in the facialrecognition system may thus comprise the device information, theauthentication images or the authentication biometrics, and theauthentication movement (path parameters).

Returning to FIG. 4, in step 430, the authentication server 120 verifiesthat the credentials received from the mobile device 112 sufficientlycorrespond with the information obtained during enrollment. For example,as shown in step 910 in FIG. 9, by using algorithms to process thecharacteristics of the face and light striking the face between thedifferent images, the authentication server 120 can determine that theface in the authentication images is three-dimensional, i.e. not arepresentation on a printed picture or video screen. Where the mobiledevice 120 sends only the authentication biometrics 120 to the server,the server 120 may validate the realness or three-dimensional aspects ofthe user imaged by comparing the biometric results of the differentimages.

In step 920, the authentication server 120 may then compare the logincredentials with the information stored from the enrollment process. Instep 920, the server 120 compares the identification of the deviceobtained during the login process to that stored during enrollment. Instep 930, the authentication biometrics may be compared with theenrollment biometrics to determine whether they sufficiently correspondwith the enrollment biometrics. In step 940, the authentication movementmay be compared with the enrollment movement to determine whether itsufficiently corresponds with the enrollment movement.

In some embodiments, a copy of the enrollment information may be storedon the mobile device 112, and the mobile device 112 may verify that thecredentials received on the mobile device 112 sufficiently correspondwith the enrollment information. This would allow a user to securedocuments, files, or applications on the mobile device 112 itself inaddition to securing a user's account hosted on a remote device, such asthe authentication server 120, even when a connection to theauthentication server 120 may be temporarily unavailable, such as when auser does not have access to the Internet. Further, this would allow theuser to secure access to the mobile device 112 itself. Or enrollmentinfo may be stored on server.

Accordingly, in step 950, if the authentication server 120 or mobiledevice 112 determines that the enrollment information sufficientlycorresponds with the credentials received, then the server or mobiledevice may verify that the identification of the user attempting logincorresponds the account holder. This avoids the cumbersome process ofthe user having to manually type in a complex password using the smallscreen of the mobile device. Many passwords now require capital,non-text letter, lower case, and numbers.

The level of correspondence required to determine that the enrollmentinformation sufficiently corresponds with the authentication informationin the login attempt may be set in advance. For example, the level ofcorrespondence may be a 99.9% match rate between the enrollmentbiometrics and the authentication biometrics and a 90% match ratebetween the enrollment movement and the authentication movement. Therequired level of correspondence may be static or elastic based on theestablished thresholds.

For example, the required level of correspondence may be based on GPSinformation from the mobile device 112. In one embodiment, theauthentication server 120 may require a 99.9% match rate as the level ofcorrespondence when the GPS information of the mobile device correspondswith the location of the user's home or other authorized location(s). Incontrast, if the GPS information shows the device is in a foreigncountry far from the user's home, the authentication server may requirea 99.99% match rate as the level of correspondence or may be deniedentirely. Hence, the required match between pre-stored authenticationdata (enrollment information) and presently received authentication data(authentication information) is elastic in that the required percentagematch between path parameters or images my change depending on variousfactors, such as time of day, location, frequency of login attempt,date, or any other factor.

The required level of correspondence may additionally depend on time.For instance, if a second authentication attempt is made shortly after afirst authentication attempt in a location far from the firstauthentication location based on GPS information from the mobile device112, the level of correspondence threshold may be set higher. Forexample, a user can not travel from Seattle to New York in 1 hour.Likewise, login attempts at midnight to three in the morning may be asign of fraud for some users based on patterns of the users' usage.

The level of correspondence between the enrollment information and theauthentication information may be the result of compounding the variousparameters of the enrollment information and the authenticationinformation. For example, when the button hold time in theauthentication information is within 5% of the button hold time of theenrollment information, the correspondence of the button hold time mayconstitute 20% of the overall match. Similarly, when the motion pathtrajectory of the authentication information is within 10% of theenrollment information, the motion path trajectory may constitute 20% ofthe overall match. Further parameter match rates such as the face sizeand facial recognition match in the authentication information ascompared to the enrollment information may constitute the remaining 10%and 50% of the overall level of correspondence. In this manner, thetotal overall level of correspondence may be adjusted (total of allparameters being more than 75%, for example), or the match rate ofindividual parameters may be adjusted. For example, on a secondattempted login, the threshold match rate of one parameter may beincreased, or the overall level of correspondence for all parameters maybe increased. The threshold match rates may also be adjusted based onthe account being authenticated or other different desired levels ofsecurity.

Returning to FIG. 4, in step 440, the authentication server 120 maygrant or deny access based on the verification in step 430. For example,if the authentication server 120 verifies that the credentials match theenrollment information, then the server 120 may authenticate the user toallow access to the user's account. In the instance where theauthentication server 120 is separate from the account server 120B (suchas a bank's server), the authentication server 120 may transmit theunique identifier to the account server along with an indication thatthe identity of the user associated with the unique identifier has beenverified. The account server 120B may then authorize the user's mobiledevice 112 to transmit and receive data from the account server 120B. Ofcourse, all this may occur at only the account server 120B or on themobile device 112 itself.

Alternatively, if the credentials provided by the user are not verified,the authentication server may transmit a message to display on thescreen of the mobile device 112 indicating that the login attemptfailed. The authentication server 120 may then allow the user to tryagain to log in via the facial recognition login system, or theauthentication server 120 may require the user to enter typical accountcredentials, such as a user name and password.

In one embodiment, the server 120 may allow three consecutive failedlogin attempts before requiring a user name and password. If in one ofthe attempts, the required level of correspondence is met, then the usermay be verified, and access may be granted. According to one embodiment,the authentication server 120 may retain the information from eachsuccessive authentication attempt and combine the data from the multipleauthentication attempts to achieve more accurate facial biometricinformation of the person attempting to authenticate. In addition, thelevel of correspondence may be increased at each successive attempt toauthenticate. In addition, by averaging the path data (authenticationmovement) and/or image data (authentication images/biometrics) fromseveral login attempts, the login data (enrollment information) isperfected and improved.

Accordingly, the above described authentication system allows forauthentication to a remote server 120 or on the mobile device 112itself. This may be accomplished as described above by the mobile device112 capturing the authentication credentials, and the authenticationserver 120 processing and analyzing the credentials compared to theenrollment information (cloud processing and analysis); the mobiledevice 112 capturing the authentication credentials and processing thecredentials, and the authentication server 120 analyzing the credentialscompared to the enrollment information (mobile device processing, cloudanalysis); or the mobile device 112 capturing the authenticationcredentials, and processing and analyzing the credentials compared tothe enrollment information (mobile device processing and analysis).

Advantages and Features of the Embodiments

The above described system provides several advantages. As oneadvantage, the facial recognition authentication system provides asecure login. For example, if during a login attempt the camera of themobile device imaged a digital screen displaying a person rotating theirhead while the phone was not moving, the accelerometer, magnetometer,and gyroscope data would not detect any motion. Thus, the enrollmentmovement and the authentication movement would not correspond, and thelogin attempt would be denied.

In addition, because a plurality of images are used as enrollment imagesand authentication images, histograms or other photo manipulationtechniques may be used to determine if a digital screen is present inplace of a human face in the images. For example, the system may checkfor light frequency changes in the captured images, or banding in animage which would indicate an electronic display generated the image,backlighting, suspicious changes in lighting, or conduct other analyseson the images by comparing the images to determine that the actual liveuser is indeed alive, present, and requesting authorization to login.

As yet another advantage, as explained above, not only must theenrollment biometrics sufficiently correspond to the authenticationbiometrics, but also the enrollment movement must match theauthentication movement, and the device information must match theenrollment device information. For example, an application may bedownloaded to a mobile device that has a digital camera. The applicationmay be a login application, or may be an application from a financialinstitution or other entity with which the user has an account. The usermay then login to the application using typical login credential such asa website user name and password. Further, the user may have a devicecode from logging in on another device, or may use the camera to scan QRcode or other such code to pair the device to their user account.

The user then holds the mobile device to move the mobile phone todifferent positions relative to his or her head while keeping his or herface visible to the camera as it is moved. As the mobile device ismoved, the camera takes the enrollment images of the face. Duringimaging, the speed and angle of the current user's mobile devicemovement is measured using the accelerometer, magnetometer, andgyroscope to generate the enrollment movement. Further continuousimaging and detection of the face throughout the process has been shownto prevent fraud. This is because a fraud attempt cannot be made byrotating images in and out of the front of the camera.

For example, a user may start the movement from right to left or fromleft to right as shown in FIGS. 6A and 6B. The movement may also be in afront and back direction as shown in FIGS. 7A and 7B. Any other movementmay be utilized such as starting in the center, then going right, andthen going back to center. Vertical and diagonal movements may also beused to further compound the complexity of the enrollment movement. Whenthe user then later attempts login, the user must repeat the motionpattern in the authentication movement to match the enrollment movementin addition to the biometric data and device information matching. Thus,the security of the system is greatly enhanced.

The system therefore provides enhanced security for authenticating auser who has a mobile device. As explained above, the system may use atleast any one or more of the following in any number of combinations tosecurely authenticate the user: physical device verification, mobilenetwork verification, facial recognition including the size of the facein the image, a face detected in every frame during the movement,accelerometer information, gyroscope information, magnetometerinformation, pixels per square inch, color bits per pixel, type ofimage, user entered code or pattern, and GPS information.

As another advantage, the facial recognition login system provides aconvenient manner for a user to login to an account with a mobiledevice. For example, once enrolled, a user does not need to enter a username and password on the small mobile device each time the user wishesto access the account. Instead, the user simply needs to image himselfor herself while mimicking the enrollment movement with the mobiledevice. This is especially advantageous with smaller mobile devices suchas mobile phones, smart watches, and the like.

The system may be further configured to allow a user to securely log onto multiple devices, or to allow users to securely share devices. In oneembodiment, the enrollment information may be stored on anauthentication server (or on “the cloud”) and thus is not associatedonly with the user's original device. This allows the user to use anynumber of suitable devices to authenticate with the authenticationserver. In this manner, a user may use a friend's phone (third partydevice) or other device to access his or her information, such asaccount information, address book information, email or other messaging,etc. by performing the authentication operation on any device.

For example, the user may provide an email address, user name code, orsimilar identifier on the friend's phone such that the authenticationserver compares the login information with enrollment information forthe user's account. This would indicate to the authentication serverwhich authentication profile to use, but does not by itself allow accessto the user's data, accounts, or tasks. Upon logging out of a friend'sphone, access to the user's information on the friend's phone isterminated. The provides the benefit of allowing a user to securelyaccess account or other authentication accessible information or tasksusing any device without having to type the user's password into thethird-party device, where it could be logged or copied. In a sense, theuser is the password.

Through cloud-based enrollment information, a single user may alsosecurely transfer data between authenticated devices. In one embodiment,a user may own a first device, such as a mobile phone, and isauthenticated on the first device via the authentication system. Theuser may then acquire a new device, such as a new phone, tabletcomputer, or other device. Using the cloud-based authentication system,the user may authenticate on the new device and transfer data from thefirst device to the new device. The transfer of data may be completedvia the Internet, a local network connection, a Bluetooth connection, awired connection, or a near field communication. The authenticationprocess may also be part of a security check to resent or restore asystem after the phone is lost or stolen. Thus, the authenticationsystem may be used to activate or authenticate a new device, with theauthentication used to verify the user of the new device.

Similarly, the system may facilitate secure access to a single shareddevice by multiple people to control content or other features on thedevice. In many cases, passwords can be viewed, copied, guessed, orotherwise detected, particularly when a device is shared by severalusers. The users may be, for example, family members including parentsand children, coworkers, or other relationships, such as students. Theauthentication system may allow each of the family members to log inbased on his or her own unique enrollment information associated with auser account.

The device may restrict access to certain content or features for one ormore of the certain user's accounts, such as children's user accounts,while allowing access to content and features for others, such as theparents' accounts. By using the authentication system for the shareddevice, the users such as children are unable to utilize a password totry and gain access to the restricted content because the authenticationsystem requires the presence of the parent for authentication, asexplained above. Thus, device sharing among users with differentprivileges is further secured and enhanced. Likewise, in a classroomsetting, a single device may be securely shared between multiple peoplefor testing, research, and grade reporting.

Adaptations and Modifications

Numerous modifications may be made to the above system and methodwithout departing from the scope of the invention. For example, theimages may be processed by a facial recognition algorithm on the deviceand may also be converted to biometric data on the device which is thencompared to previously created biometric data for an authorized user.Alternatively, the images from a device may be sent through a wired orwireless network where the facial recognition algorithms running on aseparate server can process the images, create biometric data andcompare that data against previously stored data that assigned to thatdevice.

Multiple Profiles for a Single User

Further, the photo enrollment process may be done multiple times for auser to create multiple user profiles. For example, the user may enrollwith profiles with and without glasses on, with and without otherwearable devices, in different lighting conditions, wearing hats, withdifferent hair styles, with or without facial or ear jewelry, or makingdifferent and unique faces, such as eyes closed, winking or tongue outto establish another level of uniqueness to each user profile. Such‘faces’ made by the user would not be available on the user's SocialMedia Pages and hence not available for copying, manipulation, and useduring a fraud attempt. Each set of enrollment images, enrollmentbiometrics, or both may be saved along with separate enrollmentmovement. In one embodiment at least three images are captured as themobile device completes the path. It is contemplated that any number ofimages may be captured.

Linking Enrollment Information

It is also contemplated that the enrollment process may be linked to anemail address, phone number, or other identifier. For example, a usermay sign up with an email address, complete one or more enrollments asdescribed above, and confirm the enrollments via the same email address.The email address may then further enhance the security of the system.For example, if a user unsuccessfully attempts to login via theauthentication system a predetermined number of times, such as threetimes for example, then the authentication system locks the account andsends an email to the email address informing the user of theunsuccessful login attempts. The email might also include one or morepictures of the person who failed to login and GPS or other data fromthe login attempt. The user may then confirm whether this was a validlogin attempt and reset the system, or the user may report the loginattempt as fraudulent. If there is a reported fraudulent login, or ifthere are too many lockouts, the system may delete the accountassociated with the email address to protect the user's security. Thus,future fraudulent attempts could not be possible.

Feedback Meters

To further facilitate imaging, the mobile device may include variousfeedback meters such as a movement meter or accuracy meter as shown inFIG. 10. In one embodiment, the mobile device 1012 may display amovement meter 1024 that indicates the amount of movement the mobiledevice 1012 makes as the user moves the mobile device 1012 to differentpositions relative to his/her head. For example, the movement meter 1024may be represented as a line that slides from one side of the screen. Inthis manner, the enrollment process may require a certain threshold ofdevice movement to register a user with the multi-dimensionalauthentication system. For example, the system could require that themobile device 1012 is moved in an arc or straight line and is rotated atleast 45 degrees to create the enrollment information. In anotherexample, the system could require an acceleration experienced by thedevice exceeding a threshold amount. The movement meter may also aid theuser in learning how to image himself/herself using the authenticationsystem.

The mobile device 1012 may also display an accuracy meter 1026 or anyother visual representation of authenticated frames to aid the user inauthenticating himself/herself using the authentication system andlearning to improve authentication. The accuracy meter 1026 may show auser a match rate (graphical, alpha, or numerical) of a predeterminednumber of images obtained during the authentication process. Theaccuracy meter can be represented on the display in a variety of waysincluding numeric percentages, color representation, graphical, and thelike. A combination of representations may also be utilized.

For example, as shown in FIG. 10, match rates for a predetermined numberof images taken during authentication are represented on the accuracymeter. In the embodiment shown in FIG. 10, each of the images may berepresented by a column in a graph, and the accuracy can be shown foreach image in each column. For example, the column with a longer barrepresent higher accuracy, and a column with a lower bar representslower accuracy. In addition to match rates for images, the match ratesfor the path parameter may also be displayed. Over time the user canimprove.

In another embodiment, each of the images may be represented on a tableas a color that corresponds to the match rate. The color dark green mayrepresent a very high match rate, light green may represent a good matchrate, yellow may represent a satisfactory match rate, red may representa mediocre match rate, and grey may represent a poor match rate. Othercolors schemes may also be used.

The height of the bars or the colors used may correspond topredetermined match rates. For example, a full bar or dark green may bea match rate greater than 99.9%, a three-quarter bar or light green maybe a match rate between 90% and 99.9%, a half bar or yellow may be amatch rate of 50-90%, red may be a match rate of 20%-50%, and a singleline to a quarter bar or grey may be a match rate of 0-20%. A pie chart,line graph, or any other type of representation could also be used orany other numerical or graphical display. An overall score may bepresented or a score per image.

The accuracy meter may also include a message 1028 indicating an overallmatch score. For example, the accuracy meter may indicate an averageoverall match score or the number of images which achieved a 99.9% matchrate, and display the message to a user. With the movement meter 1024and the accuracy meter 1026 as described above, the user may quicklylearn to use the authentication system due to the feedback presented bythe meters 1024, 1026.

Gamification and Rewards

The movement and accuracy meters 1024, 1026 may also be configured toincorporates game features, aspects, or techniques into theauthentication system to encourage a user to try and get the best matchpossible (such as a high number score or a high percentage of frames),increasing the user's skill in utilizing the authentication system. Thisalso builds user adoption rates for the technology.

For example, the user may compete with themselves to mimic or improvepast authentication scores to encourage or train the user to achieve ahigh score. Further modifications of the authentication meter may alsobe incorporated such as the ability to share accuracy match results withothers to demonstrate one's skill in using the system or to competeagainst others. In other instances, the user may receive a reward, suchas a gift or coupon, for high accuracy scores. While this may slightlyincrease costs, the reduction in fraud loss would far outweigh theadditional cost.

Further game techniques may be incorporated into the authenticationsystem to encourage users to take actions which will preventunauthorized or fraudulent authentication. In one embodiment, theauthentication system may award users that engage in fraud preventingactivities. One such activity is utilizing the facial recognitionauthentication system described herein. For example, based on the abovedescribed accuracy meter, the system may reward a user that successfullyauthenticates with the system above a certain match rate. The system mayaward reward points, cash, or other prizes based on the successfulauthentication or on a predetermined number of successfulauthentications. Where reward points are utilized, the points may becashed in for predetermined prizes.

Other game features may involve award levels for users who gain apredetermined amount of experience using the authentication feature. Forexample, different reward levels may be based on users successfullyauthenticating 100 times, 500 times, 1000 times, etc. Because eachinstance of fraud loss can be significant and can damage the goodwill ofthe business or organization, the benefits to fraud prevention aresignificant.

In one embodiment, the user may be notified that he or she has achievedvarious competency levels, such as a “silver level” upon achieving 100successful authentications, a “gold level” for achieving 500 successfulauthentications, or a “platinum level” for achieving 1000 successfulauthentications. An amount of points awarded for each authenticationabove a given match rate may increase based on the user's experiencelevel. Of course, the names of the levels and the number ofauthentications for each level as described above are only exemplary andmay vary as desired.

In one embodiment, an authentication only counts toward reward levelswhen business is transacted at the web site while in other embodiments,repeated attempts may be made, all of which count toward rewards.Another feature may incorporate a leaderboard where a user may benotified of a user ranking comparing his or her proficiency orwillingness in using the authentication system as compared with otherusers.

Successful use of the authentication system benefits companies andorganizations that utilize the system by reducing costs for fraudulentactivities and the costs of preventing fraudulent activities. Those costsavings may be utilized to fund the above described game features of theauthentication system.

Further activities that correspond to the authentication system andcontribute to the reduction of fraud may also be incorporated to allow auser to earn points or receive prizes. Such activities may include auser creating a sufficiently long and strong password that uses acertain number and combination of characters. This encourages andrewards users to set passwords that are not easily compromised. Otherexamples may include rewarding users to take time to performverification steps in addition to an initial authentication such as amobile phone or email verification of the authentication, answering oneor more personal questions, or other secondary verifications ascurrently known or later developed. This rewards users for taking onadded time and inconvenience to lower the risk of fraud to a company ororganization.

As another example, if the authentication service is used to login towebsites or apps that provide affiliate programs, then the reward orgift can be subsidized from the affiliate commissions on purchases madeon those sites. For example, if a commerce (product or service) web siteutilizes the method and apparatus disclosed herein to avoid fraud, andthus increase profits, then a percentage of each purchase made by a userusing the authentication service will be provided to the authenticationservice. By reducing fraud, consumer purchases are more likely andadditional users will be willing to enter financial and personalinformation. An affiliate link, code, or referral source or identifiermay be used to credit the authentication system with directing theconsumer to the commerce (product or service) web site.

Multiple Account Login

It is also contemplated that the authentication system may be configuredto allow a user to access several different web sites using a singleauthentication. Because the authentication process and result are uniqueto the user, the user may first designate which participating web sitesthe user elects to log into and then after selecting which one or moreweb sites to log into, the user performs the authentication describedherein. If the secure authentication is successful, then the user islogged into the selected web sites. In this way, the authenticationprocess is a universal access control for multiple different web sitesand prevents the user from having to remember multiple different usernames and passwords while also reducing fraud and password overhead foreach user.

Automatic Start/Stop of Imaging

It is also contemplated that the system may be configured to have thevideo camera running on the phone. The mobile device would grab framesand path parameter data when the phone moves (using the camera,gyroscope, magnetometer, and accelerometer) but only process intobiometric data on the device or send the frames up to the server if theyhave a face in them. In this embodiment, the application executing onthe mobile device could trigger the software application to start savingframes once the phone is moving and then if the phone continues to movein the correct path (a semi-circle, for example) and the system detectsa face in the frame the mobile device would start to send images, aportion of the image, or biometric data to the server for processing.When the system senses motion it may trigger the capture of images atcertain intervals. The application may then process the frames todetermine if the images contain a face. If the images do include a face,then the application crops it out and then verifies if the motion pathof the mobile device is similar to the one use used during enrollment.If the motion path is sufficiently similar, then the application cansend the frames one at a time to the server to be scanned or processedas described above.

Banding and Edge Detection

When a fraudulent attempt is made using a display screen, such as anLED, LCD, or other screen, the system may detect the fraudulent loginattempt based on expected attributes of the screen. In one embodiment,the authentication system will run checks for banding produced bydigital screens. When banding is detected, the system may recognize afraudulent attempt at a login. In another embodiment, the system willrun checks for edge detection of digital screens. As the mobile deviceis moved to obtain the authentication movement during a login attempt,the system checks the captured images to for edges of a screen torecognize a fraudulent login attempt. The system may also check forother image artifacts resulting from a screen such as glare detection.Any now know or later developed algorithms for banding and screen edgedetection may be utilized. Upon detection of fraud will preventauthentication and access to the website or prevent the transaction oraccount access.

Other Attributes Estimation

The authentication system may further conduct an analysis on theenrollment images to estimate at least one of a gender, an approximateage, and an ethnicity. In an alternative embodiment, the user maymanually enter one or more of their gender, an approximate age, and anethnicity, or this information may be taken or obtained from existingrecords which are known to be accurate. The authentication system maythen further store a user's estimated gender, age, and ethnicity asenrollment credentials or user data. Thus, when the user later attemptsto authenticate with the system, the system will compare derived gender,age, and ethnicity obtained from authentication images (using biometricanalysis to determine such data or estimates thereof based onprocessing) with the stored gender, age, and ethnicity to determinewhether to authenticate the user. For example, if the derived data forgender, age and ethnicity matches the stored enrollment credentials,then the authentication is successful, or this aspect of theauthentication is successful.

The authentication system may make the gender, age, and ethnicityestimations based on a single image during the authentication process orbased on multiple images. For example, the authentication system may usean image from the plurality of images that has an optimal viewing angleof the user's face for the analysis. In other embodiments, a differentimage may be used for each analysis of age, gender, and ethnicity whendifferent images reveal the best data for the analysis. Theauthentication may also estimate the gender, age, and ethnicity in aplurality of the images and average the results to obtain overall scoresfor a gender, age, and ethnicity.

As an alternative to obtaining the gender, age, and ethnicity asenrollment information, the estimated gender, age, and ethnicityestimations as authentication credentials may be set over a course ofrepeated use of the authentication system. For example, if in previoussuccessful authentications using biometrics and movement information,the authentication system always estimates a user's age being between 40and 50, then the authentication may set credentials for that userrequiring later login information to include images of a face estimatedto be between 40 and 50. Alternatively, gender, age, and ethnicityestimations may be implemented as one of many factors contributing to anoverall authentication score to determine whether or not to authenticatea user.

For example, if the authentication process has a gender estimation of +or −0.2 of 1.9 male rating, then if the actual results do not fallwithin that range the system may deny access for the user. Likewise, ifthe user's age range always falls between 40-50 years of age duringprior authentication attempts or enrollment, and an authenticationattempt falls outside that range, the system may deny access or use theresult as a compounding factor to deny access.

In a further embodiment, when a bracelet or watch capable of obtainingan EKG signature is used, a certain EKG signature may be required atlogin. The EKG signature could also be paired with the facialrecognition rotation to provide multiple stage sign-on for criticalsecurity and identification applications. Further, the credentials couldalso include GPS information where login is only allowed within certaingeographic locations as defined during enrollment. In one configurationthe GPS coordinates of the mobile device are recorded and logged for alogin attempt or actual login. This is additional information regardingthe location of the user. For example, if the GPS coordinates are in aforeign country known for fraud, then the attempt was likely fraudulent,but if the GPS coordinate indicate the attempt or login was made in theuser's house, then fraud is less likely. In addition, some applicationsmay only allow a user to login when at specified location such as asecure government facility or at a hospital.

The enrollment information may further include distance information.Because the motion arc (speed, angle, duration . . . ) is unique to eachuser, face detection software on the device can process the images anddetermine if the device is too close or too far from the subject. Or inother words, the enrollment information may consider the size of theface in the images. Thus, the potential enrollment information may alsovary based on the length of a user's arm, head, and face size, and onthe optics of the camera in the user's particular mobile device. Theuser may also be positioned at a fixed computer or camera, such aslaptop, desktop, or atm. The user may then move the face either forwardsand back, side to side, or up and down (or a combination) to create theimages. Hence, this method of operation is not limited to a mobiledevice. In one embodiment, the camera is disposed in an automobile, suchas in a mirror, and the person moves their head or face to authenticate.

Gradual Authentication Access

In one embodiment, the system is set to limit what the user can do whenfirst enrolled and authenticated. Then, after further authentications orafter a predetermined time period and number of authentications,additional capabilities may be granted. For example, during the first 20authentications during the first 3 months, a maximum transaction of $100may be allowed. This builds a database of known authentication datarelating to non-objected to transactions by the user. Then, during thenext 20 authentications a transaction limit of $3000 may be established.This limits the total loss in the event of fraud when the authenticationdata is limited, and the user is new to the system. For example, if anunauthorized user manages to fraudulently enroll in the authenticationsystem.

Video Display for Imaging

When the user images himself/herself using a front-facing camera, theuser may confirm that his/her face is being imaged by viewing the imageon the display, as described above. The image shown on the display maybe configured to be smaller in area than the entire display, and may bepositioned in an upper portion of the display towards the top of thedevice. When the user's image is shown only in the top portion of theuser's display screen, the user's eyes tend to look more closely at thefront camera. When the user's eyes are tracking up, the accuracy of thefacial recognition may be improved. Further, tracking the movement ofthe eyes from frame to frame may allow the system to validate that theimages are of a live person, and are not from a photograph or videorecording of the person.

The image shown on the display may also be positioned to correspond witha camera location on the user's device, as shown in FIGS. 11A-11C.Mobile devices that are available today may include front-facing camerasdisposed at several different positions. For example, one mobile device1112 a, 1112 b may have a front-facing camera 1114 a, 1114 b that isdisposed above the display and off center towards one side or the other,as shown in FIGS. 11A and 11B. Accordingly, the feedback image 1116 a,1116 b of the user shown on the display may be positioned to correspondwith the location of the camera 1114 a, 1114 b as shown. In FIG. 11A,where a camera 1114 a is above the display and is off-center at aposition left of the center, then the image 1116 a may be shown in anupper left corner of the display. In FIG. 11B, where a camera 1114 b isabove the display and is off-center at a position right of the center,then the image 1116 b may be shown in an upper right corner of thedisplay. As shown in FIG. 11C, a mobile device 1112 c may have a camera1114 c that is disposed centered directly above the display. There, theimage 1116 c may be displayed centered in an upper portion of thedisplay. In this manner, a user's eyes are directed close to and/ortrack as close to the camera as possible, aiding eye tracking andmovement verification. The user is also able to better see the feedbackimage, and other feedback or information on the screen, as they move themobile device.

The image viewed on the display by the user may further be modified suchthat the edge pixels on the sides display are stretched horizontally asshown in FIG. 12. That is, a predetermined area 1206, 1208 on both theright and the left sides are warped to stretch towards right and leftedges, respectively, of the screen. This allows a larger verticalportion of the displayed image to be shown on the display.Simultaneously, this trains a user to use the system correctly bykeeping his or her face in the center of the screen, as his or her facewould become warped on the screen if it becomes off center and part ofthe face enters the one of the warped areas.

Authentication in Low-Light Environments

To facilitate imaging, the screen on the mobile device may additionallybe displayed with a white background, and the brightness of the screenmay be increased to light up the user's face in dark environment. Forexample, a portion of the display could provide video feedback for theuser to ensure he or she is imaging himself or herself, while theremaining portion of the display is configured to display a bright whitecolor. Referring to the example shown in FIG. 11C, this may be done byshowing the video feedback 1116 c on a center of the display, with thesurrounding areas being displayed as bright white bars around the videofeedback 1116 c. In very dark situation, an LED flash on the back sideof the mobile device and the back facing camera may be used.Alternatively, the camera may be configured to create an image usinginfrared light or other night vision techniques.

When infrared imaging is used as thermal imaging, further securityenhancements are possible. Particularly, the thermal imaging may beanalyzed to indicate whether the obtained images are from an actual useror are fraudulent images from a screen or other device. When a person isin front of an infrared thermal imaging camera, the heat radiationdetected should be fairly oval shaped designating the person's head. Incontrast, the heat radiating from a screen is typically rectangular.Further, the heat patterns detected in the actual person's face as wellas the movement of the heat patterns in the images can be compared withexpected heat patterns of a human face to distinguish the images fromfraudulent authorization attempts using a screen.

Detecting Output from the Mobile Device

The display or other light source on the mobile device may further beutilized to provide additional security measures. During theauthentication process described above, light from the display or otherlight source is projected onto the user's face and eyes. This projectedlight may then be detected by the camera of the mobile device duringimaging. For example, the color tone detected on the skin, or areflection of the light from the cornea of a user's eye may be imaged bythe camera on the mobile phone. Because of this, random light patterns,colors, and designs may be utilized to offer further security and ensurethere is a live person attempting authentication and not merely an imageor video of a person being imaged by a fraudster.

As one example, when a user begins authentication, the authenticationserver may generate and send instructions to the user's device todisplay a random sequence of colors at random intervals. Theauthentication server stores the randomly generated sequence for latercomparison with the authentication information received from the mobiledevice. During authentication imaging, the colors displayed by thedevice are projected onto the user's face, and are reflected off theuser's eyes (the cornea of the eyes) or any other surface that receivesand reflects the light from the screen. The camera on the user's mobiledevice detects the colors that are reflected off the user's skin or eyes(or other surface) and generates color data indicating the colorsdetected based on the screen projection. This data may be returned tothe authentication server to determine if the color sequence or patternsent to the mobile device matches that known sequence or patternprojected by the screen of the user device. Based on this comparison atthe authentication server the authentication is a success or denied. Thecomparison with the random sequence of colors in the instructions mayalternatively occur exclusively at the user device to determine that alive user is being authenticated.

As another example, when a user begins authentication, theauthentication server may send instructions the user's device to displaya randomly generated pattern which is then stored on the authenticationserver. This pattern may include graphics, text, lines or bars, flashinglight patters, colors, a QR code, or the like. The randomly generatedpattern is displayed during authentication imaging, and the pattern isreflected off the user's eyes (cornea). The camera of the user's devicedetects the reflected pattern off the eye of the user and processes thereflected, mirrored image of the displayed pattern. The processedpattern (such as being converted to a numeric value) is transmitted tothe authentication server and compared to the pattern that was randomlygenerated and stored on the authentication server to verify if thepattern displayed by the screen, and imaged after reflection off theuser's face establishes a pattern match.

If a match occurs, this establishes or increases the likelihood that alive person is being imaged by the device. If the pattern is not amatch, or does not meet a match threshold level, then the authenticationprocess may fail (access denied) or the account access or transactionamount may be limited. It is noted that this example could also beincorporated on desktop computer with a webcam that does not incorporatethe enrollment movement and authentication movement described above.Further, this example may not only be incorporated with facialrecognition, but could also serve as an added layer of security for irisrecognition or any other type of eye blood vessel recognition, or anyfacial feature that is unique to a user.

When the above example is implemented on a desktop computer, eyetracking may also be utilized to further demonstrate the presence of alive user. For example, the screen could show a ball or other randomobject or symbol moving in a random pattern that the user watches withhis or her eyes. The camera can detect this real-time movement to verifythe user is live, and not a picture or display, and verify that the eyeor head movements correspond to and match the expected movement of theobject or words on the screen, which are known by the authenticationsystem. Eye tracking can also be done by establishing an anchor point,such as via a mouse click at a location on the screen (if the user islooking at the location where the mouse click takes place), and thenestimating where the user is looking at the screen relative to theanchor position.

The use of a moving object on the screen may also be beneficial duringenrollment on either a mobile or stationary device. For example, whilecapturing the enrollment images, the device may display a moving digitalobject (such as a circle or words(s)) that moves around the screen sothat the user is encouraged to follow it with his or her head and eyes.This movement may be involuntary from the user, or the device may beconfigured to instruct the user to follow the object. This results inmovement of the head and/or eyes creating small changes in theorientation of the user's head and face with the device camera,providing more complete enrollment information. With more completeenrollment information, the system may better ensure that the user willlater be authenticated at a high rate even at slightly different anglesduring future authentication attempts.

Intuitive User Training and Enhanced Security by “Zooming”

In one embodiment, the system is configured to aid the user to easilylearn to authenticate with the system. As shown in FIG. 13A, onceenrollment or authentication is begun as described previously, thesystem causes the user's mobile device 1310 to display a small oval 1320on the screen 1315 while the mobile device 1310 is imaging the user.Instructions 1325 displayed on the screen 1315 instruct the user to holdthe mobile device 1310 so that his or her face or head appears within inthe oval 1320. Because the oval 1320 is small, the user is required tohold the mobile device 1310 away from his or her body, such as bystraightening his or her arm while holding the mobile device 1310. Themaximum arm length and face size is unique to the user. In otherembodiment, the arm may not be fully straightened such as to accommodateoperation when space is not available, such as in a car or in a crowdedlocation. It is noted that while the small oval 1320 is shown centeredin the display, it may be positioned anywhere on the screen 1315.

Next, as shown in FIG. 13B, the system causes the user's mobile device1310 to display a larger oval 1330 on the display 1315. The display 1315may also show corresponding instructions 1335 directing the user to“zoom in” on his or her face to fill the oval 1330 with his or her face.The user does this by bringing the mobile device 1310 closer to his orher face in a generally straight line to the user's face (such as shownin FIGS. 7A and 7B) until the user's face fills the oval 1330 or exceedsthe oval. In other embodiments, the large oval 1330 may simply be aprompt for the user to bring the mobile device 1310 closer to the user'sface.

Thus, the system provides and teaches the user a simple method toprovide enrollment and authentication images along with enrollment andauthentication movement as explained above. The system may also teachvarying enrollment and authentication movement by varying the locationof the small oval 1320 on the screen 1315, and by changing the order andthe size of the ovals displayed. For example, the user may zoom in ½way, then out, then in all the way, by moving the mobile device. Thesystem may be configured to monitor that the camera's zoom function(when equipped) is not in use, which typically requires the user totouch the screen.

In one embodiment, the enrollment movement may be omitted, and theauthentication movement may be compared to expected movement based onthe prompts on the screen. For example, the device or authenticationserver generates a series of differently sized ovals within which theuser must place his or her face by moving the mobile device held in theuser's hand. In this manner, the authentication movement may bedifferent during each login depending on the order, size, and placementof the ovals shown on the screen.

The system may also incorporate other security features when the “zoomin” movement is used as shown in FIGS. 13A and 13B. Typical cameras on amobile device or any other device include a curved lens. This results ina barrel distortion effect in the resulting images taken by the camera.In some instances, this curvature may not be visible to the human eye,or may only be noticeable at certain focal lengths. The curvature orbarrel distortion effect can vary with focal length or distance betweenthe user and the lens. The degree of the barrel distortion effect isthus dependent on the type of optics used in the camera's lens and otherfactors.

The barrel distortion effect becomes more pronounced on an image of aperson's face when the person images his or her face close to the lens.The effect results in the relative dimensions of the person's faceappearing different than when the imaging is done with the person's facefarther away from the lens. For example, a person's nose may appear asmuch as 30% wider and 15% taller relative to a person's face when theimage is taken at a close proximity as compared to when the image istaken at a distance. The differences in the relative dimensions arecaused by the relatively larger differences between the camera and thevarious facial features when the person is imaged close to the lens ascompared to the relatively equal distances when the person is imaged ata distance farther from the lens.

Such differences have been found to be significant in many facialrecognition algorithms. That is, a facial recognition algorithm may notrecognize a live person imaged at a close proximity and a far proximityas the same person. In contrast, if a two-dimensional photograph of aperson is imaged by the camera at both a close proximity and a fartherproximity, the relative focal lengths between the lens and thetwo-dimensional image do not change so significantly. Thus, a facialrecognition algorithm would recognize the two-dimensional photograph asthe same person when imaged at both a close proximity and a distancefarther from the lens.

This effect may be used to increase the security of the authenticationsystem. For example, during enrollment, enrollment images may beprovided by the user at both the close and far proximity from the lens,in addition to other positions through the movement. Later, duringauthentication, authentication images may be obtained at both the closeand far distances from the lens to determine if they match with theenrollment information obtained from the enrollment images. Further,because the barrel distortion effect is expected when an actual,three-dimensional person is present, an absence of the relative changein the dimensions of the facial features alerts the system to afraudulent attempt at authentication. This effect could not easily bere-created with a two-dimensional picture (printed photograph or screen)and thus, this step can serve as a secure test to prevent atwo-dimensional picture (in place of a live face) from being used forauthentication.

In other words, using this movement of “zooming” in and out on theuser's face, two or more biometric profiles could be created for thesame person. One of the multiple profiles for the person may be imagedfarther from the camera, and one of the multiple profiles may be for theperson imaged closer to the camera. For the system to authenticate theperson, the authentication images and biometrics must match the two ormore profiles in the enrollment images and biometrics.

In addition, the system may detect the presence of a real person ascompared with a fraudulent photograph of a person by comparing thebackground of the images obtained at a close and a far proximity. Whenthe mobile device 1310 is held such that the person's face fits withinthe oval 1320, objects in the background that are almost directly behindthe person may be visible. However, when the mobile device 1310 is heldsuch that the person's face fits within the larger oval 1330, theperson's face blocks the cameras ability to see the same objects thatare almost directly behind the person. Thus, the system may compare thebackgrounds of the images obtained at the close and the far proximity todetermine whether the real person is attempting authentication with thesystem.

Of course, in FIGS. 13A and 13B, shapes or guides other than ovals 1320and 1330 may be used to guide the user to hold the mobile device 1310 atthe appropriate distance from his or her face. For example, the mobiledevice 1310 may show a full or partial square or rectangle frame.Further, the system may vary the size and location of the frame, such asthe ovals 1320, 1330 to add further security. For example, the systemmay require a medium sized frame, a small frame, and then a large frame.As another example, the system may require a small frame at a firstlocation and a second location, and then a large frame. This may be donerandomly to teach different users different enrollment andauthentication movements.

The number of frame sizes presented to the user may also vary for asingle user based on the results of other security features describedherein. For example, if the GPS coordinates of the mobile device showthat the device is in an unexpected location, more frames at differentdistances may be required for authentication. One or more indicators,such as lights, words, or symbols may be presented on the screen to bevisible to the user to direct the user to the desired distance that themobile device should be from the user.

In FIGS. 13A and 13B, the system may predict the expected barreldistortion of the images based on the mobile device used for enrollmentand authentication, and based on known and trusted enrollment data. Inaddition or as an alternative, the known specifications of a mobilephone camera for a given model may be utilized to predict the expecteddistortion of the person's facial features at different distances fromthe lens. Thus, the authentication may be device dependent. Further,enrollment information from the user is not required at every possibledistance from the camera.

For example, as described above, enrollment images and biometrics may beobtained for a user at two distances from the user. Duringauthentication, multiple images are captured in addition to imagescorresponding the close and far distances of the enrollment images andbiometrics. Based on the expected distortion of these intermediaryimages according to the distanced traveled by the device, the system mayvalidate that the change in distortion of the images is happening at thecorrect rate, even though only two enrollment profiles are obtained.

The capturing of these images may be still images or video, such thatframes or images are extracted from the video that is taken during themovement from the first position distant from the user and the secondposition proximate the user. Thus, it is contemplated the operation maycapture numerous frames during the zoom motion and ensure that thedistortion is happening at the correct rate for the head size and themovement of the mobile device distance based on data from theaccelerometers, magnetometers, and so forth.

Over time based on accumulated data, or calculated data during designphase, the system will have data indicating that if a phone is moved acertain distance toward a user's face, then the distortion effect shouldfall within a known percentage of the final distortion level or initialdistortion level. Thus, to fool or deceive the authentication systemdisclosed herein, the fraud attempt would not only need to distort thefraudulent two-dimensional picture image, but would also need to cut thebackground, and then make a video of the face, distortion, andbackground that does all of this incrementally and at the correct speed,all while not having any banding from the video screen or having anyscreen edges visible, which is very unlikely.

Many currently known facial detection and facial recognition algorithmsare configured to look for a small face within an image. Thus, to ensurethat the facial detection and recognition algorithms detect andrecognize the user's face in the zoomed in image (FIG. 13B), the systemmay add a large buffer zone around the image taken at a close proximity.This creates a larger overall image and allows current facial detectionand recognition algorithms to detect and recognize the face, even wherethe face of the user is large in the original image.

When the enrollment and authentication movement resulting from theprocess described with FIGS. 13A and 13B is used, the eye trackingsecurity features described above may also be enhanced. For example,when the user is instructed to bring the mobile device 1310 closer tohis or her face to fill the oval 1330, the QR code, a random shape, abar code, color, text, numbers or any other visual indictor may bedisplayed on the screen. At this close distance, the reflection of thedisplayed indicator off the user's eye or face may be more easily imagedby the camera. Furthermore, eye movement, blinking, and the like todetermine the “liveness” of the person being imaged may also be moreeasily obtained at the close proximity.

In one embodiment, at least one blink is required to prove liveness forauthentication. In another embodiment, blinks may be counted, and thenumber of blinks may be averaged over time during authentications. Thisallows for an additional factor in authentication to be the number ofblinks observed during the motion. If a pattern of when the user blinksduring the motion is observed, the system may verify that the userblinks at the expected time and device location during the motion duringfuture authentication attempts.

In other embodiments, the size or location of the oval or frame maychange to sizes or locations other than that shown in FIGS. 13A, 13Bsuch that the user must position and/or angle the phone to place his orher face within the oval. This establishes yet another method ofinsuring liveness of the user.

In one exemplary method, the mobile device is positioned at a firstdistance from the user and a first image captured for processing. Thisdistance may be linearly away from the user and in this embodiment notin an arc or orbit. This may occur by the user moving the mobile device,either by hand, or by the mobile device being on a movable device orrail system. Or, the lens system may be adjusted if in a fixed system tochange the size of the user's face in relation to the frame size.Alternatively, the user may stay stationary, the multiple cameras may beused, or camera may move without the user moving. Once some form ofmovement (from a device, camera, lens, or user) has occurred toestablish the camera at a second distance, a second image is capturedfor processing. Movement from the first position to the second positionmay be straight toward the user. Processing occurs on both images.

The processing may include calculations to verify a difference betweenthe two images, or a difference in biometrics obtained from the twoimages, that indicates that a real person is being imaged. Processingmay occur to compare the first authentication image to a firstenrollment image (corresponding to the first distance) to determine if amatch is present and then compare the second authentication image to asecond enrollment image (corresponding to the second distance) todetermine if a match is present. If a match occurs, then authenticationmay proceed.

Variations on these methods are also possible with the system requiringa match at the first distance, but a failure to match at the seconddistance, thereby indicating that the second image is not of atwo-dimensional picture. The processing resulting in a match or failureto match may be any type image or facial recognition processingalgorithm. As with other processing described herein, the processing mayoccur on the mobile device, one or more remote servers, or anycombination of such devices.

All the processing described herein may occur on only the mobile device,only a remote server, or a combination there. The biometric data may bestored on the mobile device or the server, or split between the two forsecurity purposes. For example, the images could be processed on themobile device, but compared to enrollment data in the cloud or at aremote server. Or, the images could be sent to the cloud (remote server)for processing and comparison.

Touch Screen Enhancements

Additional added security modifications may include information about auser's finger. Many mobile devices with touch screens can detect thelocation and approximate size of a user's touch on the screen.Accordingly, an approximate size of a user's finger or thumb may bemeasured by the system. In addition to the size of a finger, anorientation angle of the finger or whether the fingers or thumbs of theright or left hand are used can be detected.

In one embodiment, a user selects an account to open, begins enrollmentimaging, or begins authentication imaging by touching the touchscreen ofthe user device. The authentication system may thus detect whether thetouch by a user during authentication corresponds with previously storedenrollment information including the size of the user's finger or thumb,amount of pressure applied to the screen and whether the user is rightor left handed. This adds an additional security layer for theauthentication system.

Furthermore, the authentication system may require that the userinitiates an authentication by touching a fingerprint reader or thetouchscreen in one or more predetermined manners. In one embodiment, asshown in FIG. 14, a touchscreen 1410 may be divided up intopredetermined regions 1420. For example, there may be nine equal,circular, square, or other shaped regions 1420 on the touchscreen 1410of the mobile device. During enrollment, the user selects one of theregions 1420 of the screen 1410 to touch to initiate authentication.During authentication, if the preselected region 1420 is not touched tobegin authentication or during the entire authentication process, thenauthentication is denied. This is but one possible design possibilityand other design options are contemplated.

The regions 1420 on the touchscreen may be visually represented by agrid, or may not be displayed at all on the touchscreen 1410. As shownin FIG. 15, in addition to or in place of the regions 1420, buttons 1520may be displayed on a touchscreen 1510. Here, the user may initiate theauthentication by pressing one or more of the buttons 1520 in apredetermined pattern. The user may also initiate authentication via apredetermined swiped pattern. The position to be touched by the user maychange with each authentication attempt and may be conveyed to the userthrough any instructions from the authentication server, such as a code,number, letter, color, captcha or other indicator.

Voice Parameters

It is also contemplated that the user could record their voice byspeaking a phrase while recording their images during the enrollmentprocess when first using the system. Then, to authenticate, the userwould also have to also speak the phrase when also moving the mobiledevice to capture the image of their face. Thus, one additional pathparameter may be the user's spoken voice and use of voice recognition asanother layer or element of the authentication process.

Image Quality Assurance

The authentication system may also process the images received from themobile device to determine if the images are of sufficient quality. Forexample, the system may check the images for blurriness caused by theimages being out of focus or by the camera lens being obscured byfingerprints, oils, etc. The system may alert that user that the qualityof the images is insufficient (or too bright or too dark) and direct theuser to adjust a focus, exposure, or other parameter, or to clean thelens of the camera.

Autofocus

The authentication system may also utilize an autofocus feature when themobile device camera is equipped with such. For example, when an actual,three-dimensional person is being imaged, the system checks to ensurethat the sharpness of the image changes throughout as the camera performauto-focusing. In another embodiment, the system may control theautofocus so that the camera focuses on a first location or distance tocheck for sharpness (in focus) of a portion of the image containing aface. The system then controls the camera to focus at a second locationor distance where the presence of a face is not detected and check forsharpness (in focus) of a portion of the image. If a three-dimensionalperson in a real environment is being imaged, it is expected that thefocal length settings should be different at the first and secondlocations, which suggests a real person is presently being imaged.However, if the focal lengths of both locations are the same, thisindicates that a two-dimensional photograph or screen is being imaged,indicating a fraudulent login attempt.

The system may also control the auto-focus of the device to check fordifferent focal lengths of different features in the image. For example,when a person's face is imaged from the front, a person's ear isexpected to have a different focal length (more distant) than the tip ofa person's nose.

Images of Login Attempt

The authentication server may also be configured to store theauthentication images for a predetermined length of time. The images mayprovide additional security benefits as evidence of a person attemptingto log in to a user's account. For example, the system may store apredetermined number of prior log in attempts, such as twenty loginattempts, or store images from login attempts for a predetermined timeperiod, such as during the past seven days or weeks. Any fraud orattempted fraud will result in pictures of the person attempting thelogin being stored or sent to the authentication server of the accountserver.

The mere knowledge that photos will be taken and sent is a significantdeterrent to any potentially dishonest person because they know theirpicture will be taken and stored, and it is an assurance of security tothe user. Likewise, any attempted and failed attempt can have the photostored and indicator of who is attempting to access the account. It isalso contemplated that an email or text message along with the pictureof the person attempting the failed log in may be sent to the authorizeduser, so they know who is attempting to access their account. Thisestablishes the first line of security for the account as the user withthe photo or image also being possessed by the authentication server.

Adaptive Match Thresholds

Further, the level or percentage of correspondence between theenrollment information and the authentication information toauthenticate the user may change over time. In other words, the systemmay comprise an adaptive threshold.

After a user regularly uses the authentication system described above,the user will have logged in with the system by moving the mobile devicein the predetermined path relative to his or her head many times.Accordingly, it may be expected that as the user will gain experienceusing the authentication system, and that the user will gradually settleinto a comfortable and standardized motion path. In contrast, theinitial enrollment movement of a user will likely be the most awkwardand clumsy movement as the user has little experience with theauthentication system.

To make the authentication system more convenient for the user withoutlosing security, the adaptive threshold system allows the enrollmentmovement to adapt so that the user is not locked into the awkward andclumsy initial movement as the enrollment movement. To facilitate this,upon each successfully authorization, the successful authorizationmovement is stored, and the motion path is added to a list of acceptablemotion paths. The list of acceptable motion paths may be limited to apredetermined number of paths. When a new successfully authorization iscompleted and the list of acceptable motion paths is full, the olderenrollment motion path is deleted and the newest is stored in its place.Alternatively, the motion path that is least like the other motion pathsstored on the list may be deleted. Thus, by storing the most alike ornewest motion paths, the enrollment movement may slowly adapt over timeas the user because familiar with the system and settles into acomfortable motion path for authentication.

In addition, other enrollment information may adaptively change in asimilar manner as the user information. For example, successfulauthentication photos or biometric information can be stored as part ofthe enrollment information, and old enrollment information may bediscarded over time. In this manner, the authentication system can beconvenient for a user even over a long period of time as the userexperiences aging, facial hair growth, different styles of makeup, newglasses, or other subtle face alterations.

Determining how much variance is allowed over time in the motion path orthe biometric information, or both may be set by the entity requiringauthentication to meet that entity's security requirements. Time ornumber of scans after the initial enrollment can be used to modify theadaptive threshold. For example, during a first few days afterenrollment, the threshold may be lower while a security threat is lowand the differences in paths are likely to be higher. After severalauthentications or several days, the threshold may increase. Thethreshold further may be set based on trending data of either the motionpath or biometric information. For example, the threshold may be morelenient in a direction the data is trending, while having a tightertolerance for data against the trend.

A temporal aspect may also be added along with the location information.For example, if the user conducts and authenticates a transaction nearhis home, and then one hour later another transaction is attempted in aforeign country, the transaction may be denied. Or it may be denied ifthe distance between the prior authentication location and the nextauthentication location cannot be traveled or is unlikely to have beentraveled in the amount of time between login or authentication attempts.For example, if the user authenticates in Denver, but an hour later anattempt is made in New York, Russia or Africa, then either first orsecond attempt is fraudulent because the user likely cannot travelbetween these locations in 1 hour.

Further, if the next transaction is attempted at a more reasonable timeand distance away from the first transaction, the level ofcorrespondence threshold may be raised to provide added security,without automatically denying the transaction. Likewise, an altimetermay be used such that if the altitude determined by the mobile device isdifferent than the altitude of the city in which the user is reported tobe located, then this may indicate a fraud attempt. Thus, altitude orbarometric readings from the mobile device may be used to verifylocation and can be cross referenced against GPS data, IP address orrouter location data, or user identified location.

Random Image Distortion

To provide an additional layer of security to the facial recognitionauthentication system, the system may utilize random image distortion.For example, a user may be assigned a random distortion algorithm uponenrollment into the system. The distortion algorithm may include suchdistortions to the image as widening or narrowing the person's face by apredetermined amount, adding or superimposing a predetermined shape at apredetermined position on the user's face. As one example of this, thedistortion may be a circle superimposed at 100 pixels above the user'sleft eye.

With the uniquely assigned distortion on the images from the user, thebiometric data for that user will be unique to the account or deviceused by the user. That is, the enrollment biometrics stored on theauthentication server or on the mobile device will reflect not only thefacial features of the user, but also will reflect the uniquely assignedimage distortion. Thus, even if an accurate, fraudulent representationof a person were used on a different device or via a different account,the proffered authentication biometrics would not sufficientlycorrespond due to a different or an absence of the unique distortion.Thus, the overall security may be enhanced.

Security Layers

It is noted that each of the above embodiments, modifications, andenhancements may be combined in any combination as necessary to createmultiple layers of security for authentication. For example, the facialrecognition may be combined with motion detection or path detection, oroperate independently of these features for authentication. Further,when more than one of the above described enhancements or modificationsare combined, the authentication system may be configured so as not toprovide any feedback or indication on which layer failed authentication.

For example, when a predetermined touch pattern to initiateauthentication is combined with the authentication movement and facialauthentication, the system does not indicate whether a touch pattern wasincorrect, or the authentication movement or authentication imagesfailed to correspond to the enrollment information. Instead, the systemprovides an identical denial of authentication no matter what failureoccurs. This is the case when any number of the security featuresdescribed above are combined. In this manner, it is difficult for afraudster to detect what aspect of the fraudulent credentials must becorrected, further enhancing the security of the system.

All the above features may be incorporated together, or only somefeatures may be used and others omitted. For example, when the deviceprompts the user to move the device so that the user places his or herhead within a first small frame (such as an oval) then to a second largeframe (such as in FIGS. 7A, 7B, 13A, and 13B), the system may beconfigured such that facial recognition need not be performed on theimage(s) in the first frame (distantly captured frames). The security ofthe system is maintained by performing facial recognition throughout theimaging at some point between the first and second frames, and at thesecond frame. This may especially be true when also integrated anotherlayer of security, such as checking eye tracking following a movingobject on the screen, or reading a reflection of a QR code or randomshape off the user's eye. In another embodiment, when two or morecameras are used creating three dimensional, stereoscopic images, thefacial recognition may not be performed at the first, far away frame,but instead the liveness of the person may be validated at the closer inframe only after the movement of the device. In still other embodiments,other security layers may be used, and the motion parameters may beomitted. Such combinations may be beneficial for larger or stationarydevices, such as gaming laptop computers, personal desktop computers, astationary kiosk, or the like.

Example Applications

Likewise, although described herein as financial account authentication,the authentication using path parameters and image data may beimplemented in any environment requiring verification of the user'sidentity before allowing access, such as auto access, room access,computer access, web site or data access, phone use, computer use,package receipt, event access, ticketing, courtroom access, airportsecurity, retail sales transaction, IoT access, or any other type ofsituation.

For example, an embodiment will be described where the aboveauthentication system is used to securely conduct a retail salestransaction. In this embodiment, a user is enrolled with theauthentication server or an authentication application on the mobiledevice as described above and has generated enrollment informationincluding enrollment images and/or biometrics, and enrollment movement.In this example, the user initiates or attempts to complete atransaction at a retail establishment with a credit card, smart card, orusing a smart phone with NFC capabilities.

The user begins the transaction by swiping a credit card, smart card, orusing an application on a smartphone with NFC capabilities to pay forgoods or services. The retail establishment would then authorize thecard or account with the relevant network of the financial institution(“Gateway”). For example, the retail establishment, through a Gatewaysuch as one operated by VISA or AMERICAN EXPRESS would determine whetherthe account is available and has sufficient available funds.

The Gateway would then communicate with the authorization server toauthorize the transaction by verifying the identity of the user. Forexample, the Gateway may send an authorization request to theauthentication server, and the authentication server then sends anotification, such as a push notification, to the user's mobile deviceto request that the user authenticate the transaction.

Upon receipt of the notification from the authentication server, such asthrough a vibration, beep, or other sound on the mobile device, the usermay then authenticate his or her identify with the mobile device. Theauthentication server may also send information concerning thetransaction to the user for verification by the user. For example, theauthentication server may send information that causes the mobile deviceto display the merchant, merchant location, and the purchase total forthe transaction.

Next, as before, the user may hold the mobile device and obtain aplurality of authentication images as the user moves the mobile deviceto different positions relative to the user's head. While moving themobile device to obtain the authentication images, the mobile phonefurther tracks the path parameters (authentication movement) of themobile device via the gyroscope, magnetometer, and the accelerometer toobtain the authentication movement of the device. The mobile device maythen send the device information, the authentication images, and theauthentication movement to the authentication server. In otherembodiments, the mobile device may process the images to obtainbiometric data and send the biometric data to the server. In still otherembodiments, the mobile device may process the images, obtain theauthentication information, compare the authentication information toenrollment information stored on the mobile device, and send pass/failresults of the comparison to the authentication server.

The authentication server may then authenticate the identity of the userand confirm that the user wishes to authorize the transaction on his orher account if the device information, authentication images and/orbiometrics, and authentication movement correspond with the enrollmentdevice information, the enrollment images and/or biometrics, and theenrollment movement. The authentication server then transmits anauthorization message to the Gateway. Once the gateway has receivedconfirmation of the authorization, the Gateway then communicates withthe retail establishment to allow the retail transaction.

Several advantages may be obtained when a retail transaction isauthorized utilizing the above system and method. Because the identityverification of the user and the confirmation of the transaction iscompleted via the authentication system and mobile device, there is nolonger a requirement for a user to provide his or her credit card orsignature, or to enter a pin number into the retailer's point of salesystem. Further, the retail establishment does not need to check a photoidentification of the user. The above method and system also has theadvantage that it provides secure transactions that can work with mobileand online transactions that do not have cameras, such as securitycameras, on the premises.

In the secure retail transaction described above, the user obtains thetotal amount due on his or her mobile device from the retailestablishment via the Gateway and authentication server. However, in oneembodiment, the mobile phone may use the camera as a bar code, QR code,or similar scanner to identify the items and the prices of the itemsbeing purchased. The mobile device may then total the amount due and actas the checkout to complete the transaction with the retailestablishment.

In another embodiment, a user of the application may want to anonymouslypay an individual or a merchant. In this instance, the user woulddesignate an amount to be paid into an application, and the applicationwould create a unique identifying transaction number. This number maythen be shown to the second user, so the second user can type theidentifying transaction number on an application on a separate device.The unique identifying transaction number may also be sent from the userto the second user via NFC, Bluetooth, a QR code, or other suitablemethods. The second user may also type the amount and request payment.

Upon receiving the payment request and unique identifying transactionnumber, the authentication server may send a notification to the firstuser's mobile device to authenticate the transaction. The user wouldthen verify his or her identity using the facial recognitionauthentication system described above. The user may alternatively oradditionally verify his or her identity using other biometric data suchas a fingerprint or retina scan, path based motion and imaging, or theuser may enter a password. Upon authentication, the user's device wouldsend a request to the user's payment provider to request and authorizepayment to the second user. In this manner, the payment may be donesecurely while the users in the transaction are anonymous.

According to one embodiment, as an additional measure of security, theGPS information from the mobile device may also be sent to theauthentication server to authenticate and allow the retail transaction.For example, the GPS coordinates from the mobile device may be comparedwith the coordinates of the retail establishment to confirm that theuser is actually present in the retail establishment. In this manner, acriminal that has stolen a credit card and attempts to use the card froma distant location (as compared to the retail location) is unable tocomplete a transaction because the user's phone is not at the locationof the retail establishment. IP addresses may also be used to determinelocation.

As explained above, the level or percentage of correspondence betweenthe enrollment information and the authentication information toauthenticate the user may also be adjusted based on the coordinates ofthe GPS of the mobile device. For example, if the retail establishmentand GPS coordinates of the mobile device are near a user's home, thenthe level of correspondence may be set at a lower threshold, such as ata 99% match rate. Alternatively, if the location is very far from theuser's home, and is in a foreign country, for example, then the level ofcorrespondence may be set at a higher threshold, such as at a 99.999%match rate.

Biometric Identification Using Root Identity Information

Most biometric identification systems in recent years use devices suchas smartphones to capture biometric data (e.g. a digital photograph orscan of a fingerprint). This biometric data is matched to preexistingbiometric data either on the device (in compliance with the FIDOAlliance standards) or on the cloud (a remote computing device) wherethe biometric data is sent to servers and compared to preexisting data.

However, with the ability to convert images or other biometric data intobiometric templates on the device without sending the raw data files upto a server, an additional option is available. Existing raw biometricdata such as facial images, fingerprint scans, etc. or convertedbiometric templates may be downloaded to the device. The downloadedbiometric data may then be converted and/or compared to a biometrictemplate that was created from the data captured on that device andpreviously uploaded to the cloud or captured and uploaded to the cloudfrom a different device.

This allows a third party to provide an existing root identity profilefor comparison to the biometric information obtained at the device forauthentication. For example, the root identity profile may comprise animage or other biometric reading from a customer that was captured andverified in a bank branch, from a DMV file, or from another authorizedand trusted source. The root identity profile may alternatively oradditionally comprise biometric templates created from the verifiedimage or biometric reading. In this manner, the identification match atthe device has in increased level of trust based on the verified,third-party root identity profile.

FIG. 16 shows a system for biometric identification using root identityinformation, according to an exemplary embodiment. The system includes auser device 1612 such as a smart phone or tablet computing device thatcomprises one or more biometric sensors such as a camera 1614 andfingerprint scanner 1615. The device 1612 communicates with a network116 such as the Internet.

A root identity server 1630 is also connected to the network 116. Theroot identity server 1630 may be a bank server, a government server, orother “trusted” server that stores the root identity informationincluding biometric information and/or biometric template(s). The rootidentity server 1630 is connected to biometric sensing devices such as acamera 1632 or fingerprint scanner 1634. An authentication server 1620providing an application such as facial recognition algorithms and thelike is also connected to the network 116.

FIG. 17 shows a method for authenticating using a root identificationsystem, according to one exemplary embodiment. Authentication usingfacial recognition as the biometric information analyzed for a rootidentity profile may work as explained in the following exemplaryembodiment. First, in step 1701, biometric information is captured via atrusted device (camera 1632 or scanner 1634 in FIG. 16). The device isconsidered trusted because the biometric information collected at thedevice is verified by a trusted institution such as a bank or governmentagency. A root identity profile is established in step 1703 thatcomprises the biometric information from the trusted device and linksthe biometric information to a user identity. This root identity profileis stored on the server, such as server 1630.

In step 1705, biometric information such as an image that contains dataabout the face of an individual from the root identity profile is sentfrom the server 1630 to the smart device 1612 upon an authenticationrequest from the smart device 1612. The user of the smart device 1612then articulates the camera 1614 so that the user's face can be capturedby the device's camera 1614, in step 1707. The image downloaded from theserver 1630 and the image that has been captured on the device 1612 cannow be compared in step 1709. For example, each image is converted intoa biometric template by a facial recognition algorithm for comparison.Upon comparison, if the templates are similar enough based on thethresholds set by, for example, an application publisher, the devicecaptured image (device identity) and the previously captured image (rootidentity) can be considered a match in step 1711. Access may then begranted, or the signup/enrollment process may then be completed based onthe matching images in step 1713. If there is no match in step 1711, theaccess is denied in step 1715.

The benefits of this system include but are not limited to the abilityto match previously captured biometric data from a different device witha new device while no Biometric Data leaves the new device during thematching. This is important in some regulatory environments andindustries.

For facial recognition systems with a server component, the same facialrecognition algorithm can be loaded onto the server as is running in anapplication on the smart device. This allows only the template to betransferred to the device instead of the biometric reading itself (e.g.the facial images, fingerprints scans, etc.). For example, in step 1705,the biometric information may be the biometric template instead of animage from the root identity profile. The algorithms must be configuredso that the templates they create are homogenous and can be compared.That is, if the algorithms output data in different formats, theresulting biometric templates/data format is incompatible, and nomatching can occur because the similar facial features would not berepresented by similar biometric template data patterns. The termtemplate is defined herein as biometric data points represented by astring of numbers or other data formed in a consistently formattedpattern so that similarities and differences may be determined viavarious methods of comparison.

In an embodiment where on the template is transferred to the device, theroot identity established in step 1703 may include a biometric templatecreated from a biometric algorithm, such as a facial recognitionalgorithm. For example, an image that includes the face of an individualthat captured with a trusted device (camera 1632 at a bank branch, DMV,etc.) is sent to the server 1630 where it is converted to a biometrictemplate with a facial recognition algorithm. As mentioned above, thebiometric template from the root identity profile is sent to the smartdevice 1612 upon an authentication request in step 1705. This can bereferred to as the root identity biometric template. The method proceedsas previously explained with reference to FIG. 17, where the biometrictemplates are compared in step 1709.

In another example, two or more biometric modalities could be usedtogether such as fingerprints, face, and voice. Another example of themethod of FIG. 17 using two or more biometric modalities may work asfollows. First, images of a user's face, scans of the user'sfingerprints, as well as a recording of the user's voice are capturedwith trusted devices in step 1701 (e.g. devices 1632, 1634 at a bankbranch, a DMV, etc. where the identity of the captured data is verified)to establish a root identity in step 1703. The images, scans, andrecording may be considered root identity biometric data because thisinformation is captured from a trusted source. In step 1707, the user ofthe smart device (1) presses one or more of his/her fingers on afingerprint sensor, and/or takes a photo of their fingers; (2)articulates the camera so that the user's face can be captured by thedevice's camera; and/or (3) speaks words into the device's microphone tobe recorded. The device recorded data may be considered device identitybiometric data.

The root identity biometric data and the device identity biometric dataare converted into biometric templates (root identity biometrictemplates and device identity biometric templates) by fingerprintrecognition, facial recognition, and/or voice recognition algorithms. Insome instances, the root identity biometric data may be converted intothe root identity biometric templates at the server, and the templatesmay be sent to the device. The root identity biometric templates and thedevice identity biometric templates are compared in step 1709, and ifthe templates are similar enough based on the thresholds set by, forexample, an application publisher, the root identity templates and thedevice identity templates can be considered a match. Based on the match,access may be granted, or a signup/enrollment process can be completedin step 1713.

In another embodiment, in step 1709, the images and/or the biometrictemplate(s) from the user's device may be uploaded to the server wherethey can be stored and/or compared with the root identity biometricimages and/or template(s). Then, if the user wishes to replace theoriginal device or add a second user device to the account, both theroot identity image(s) and/or template(s) the device identity image(s)and/or template(s) captured on the first device can be sent to thesecond device during set up or enrollment for comparison and matching.This daisy-chains the root identity from the server to the first deviceidentity, and then again to the second device identity. If no rootidentity image and/or template has been captured previously and storedon the server, the image and/or template that is uploaded from the firstdevice can still provide added security. If the user chooses to add asecond device to an account, the image(s) and/or template(s) from thefirst device can be downloaded to the second device, and the comparisondescribed above may again occur. This allows the user to add a seconddevice with increased security because the user identities on bothdevices were deemed to be a match.

In addition, when the image(s) and/or template(s) are uploaded to theserver, the on-server comparisons between the image(s) and/ortemplate(s) can be performed independent from a comparison performeddirectly on the device. This offers a significant increase in securitybecause even if a hacker was somehow able to manipulate the user'sdevice to send a “Match” result back to the server, the server wouldalso compare the same image(s) and/or biometric template(s). Hence, theauthentication may occur at two or more devices or servers to make thesystem more secure. If less than all or a predetermine number ofdevice/serves to not authenticate, then a match is not declared. Thus,the server would also need to determine that the image(s) and/orbiometric template(s) were a match using the same thresholds. Therefore,the hacker would not only need to compromise the user's device, but alsothe one or more servers to defeat the security.

In addition to the biometric matching, liveness checks may be includedon the device portion of the matching as well as the server portion, ashave been described in detail above. For example, additional informationsuch as device movement, skin texture, three-dimensional depthinformation can be used to help determine that the biometric data beingpresented to the camera is from a live human being and not a photo,video, or mask spoof.

Remote Collection of Biometric Images/Templates

To verify biometric data, an individual typically is required to enter abank branch, a government office such as a DMV or police station, orother “trusted” location to have his/her biometric data collected. Forexample, a bank may require a photograph, a fingerprint, or a voicerecording to open certain types of accounts. The obtained biometric datais then linked to the person and the account. This in-person collectionof biometric data has typically been required because there was no otherway to trust that an individual was indeed who they claimed to be.Through the in-person collection, the identification is verified by, forexample, the person providing documents with their name and photographissued by a governing body.

However, according to an exemplary embodiment disclosed herein, anindividual may provide his/her own biometric data using any smart devicewith a biometric sensor or camera to be verified without in-personverification. In fact, according to the disclosed embodiments, accountproviding or financial institutions may trust with more certainty thanever before that the biometric data provided is from the correctindividual and not an imposter, hacker, or bad actor.

FIG. 18 shows a method of remotely establishing a biometric identity,according to one exemplary embodiment. In this embodiment, an individualfirst downloads an application to his/her smart device from aninstitution with which he/she either has an account, or with whichhe/she wants to open an account in step 1801. Upon opening theapplication and when prompted, the person presents his/her face,fingerprint, etc. to the camera or sensor. The biometric data iscaptured and stored on the device as “enrollment data” in step 1803. Insome embodiments, the enrollment data is sent to the server.

Next, the user makes a payment or a deposit to the institution in step1805. For example, if a lending institution has provided a mortgage tothe user, then the user would enter his/her payment account informationinto the application so that the institution could collect payment. Whenthe payment information and authorization is transmitted to the lendinginstitution some or all of the biometric enrollment data from the useris collected and is transferred to the lending institutions server withit. Because the payment is made by the user for the user's debt, whichcauses money to flow away from the user and thus would not occur by apotential hacker or person committing fraud, the resulting biometricdata collected as part of the transaction is considered as trusted.

Later, when the user again opens the application to conduct anothertransaction, the user is again prompted to present his/her biometricinformation to the camera or sensor, and new biometric templates can becreated in step 1807. The new biometric templates are compared to theprevious “enrollment data” on the device and/or the new templates can besent to the server for comparison in step 1809. In some embodiments, thedevice may compare the templates by downloading the enrollment datatemplates from the server to the device for matching.

When it is determined that the new biometric information and/ortemplates do not match the enrollment data, then the transaction may bedenied as shown in step 1811 and the root identity will not have theunmatched biometric data added to it. However, when the new biometricinformation sufficiently matches the enrollment data, the transactionmay be authorized as shown in step 1813. Furthermore, when there is amatch, the trust level of the biometric data appended to the user'sprofile is increased.

Because the user is sending funds into the account, for example to pay adebt or to make a deposit, he/she has an incentive to be able to lateraccess the account that contains those funds or that has had debtreduced. Thus, over time as several deposits and/or payments are madewith matching biometric templates, the trust in the identity of the userperforming the transactions increases as shown in the loop of steps1807, 1809, and 1813.

To limit liability, access of withdrawals can be limited to the sameamount or less than has been deposited or paid in total by the user. Forexample, if a user pays a $3,000 mortgage payment each month for threemonths using his/her smart device and using his/her face to identifythemselves each time, the lending institution may be willing to allowthat person to transfer up to $9,000 from a different account that thebank has for the user, such as a checking account.

As banks and other lending institutions report on outstanding balances,credit limits, and payment timeliness to the credit bureaus, it isenvisaged that the bank could also provide the biometric template(possibly in an encrypted format) to the credit bureau to store as partof the identifying information in the user's credit file. Then if theuser desires to apply for credit from a different institution thatinstitution can require that the user access their version of theapplication with the same biometric data collection system as was usedto create the template. The biometric templates could be sent to thecredit bureaus servers and be compared with the templates on file forthat individual. With this process, the user can positively identifythemselves and grant access to the financial institution to view theircredit information without providing or transmitting their socialsecurity number, date of birth or other sensitive information.

If a user does not have a debt to pay to the account issuer or theissuer is not a financial institution, it is possible to simply offer atemporary escrow service to provide the assurance that the biometricdata provided is true and correct for the user being claimed. Forexample, a user can provide a credit card number with his/her name andaddress, the card could be billed $100 and the user would provide theirbiometric data to the app in their smart device. The user would thencorrectly answer a series of knowledge based authentication questionsbased on their credit report, insurance information, medical informationor other potential confidential information, and provide their biometricdata again to the app to retrieve the funds. The result is a biometricidentity that can be trusted in future transactions up to the amountthat was previously placed into escrow and successfully retrieved.

Decentralized Biometric Identity Ledger

There are numerous security and privacy benefits to a decentralized,anonymous, biometric identity network as compared to biometricauthentication conducted on a centralized database or solely on a userdevice. As previously explained, biometric identity information maycomprise images having biometric data such as digital photographs of aface or a fingerprint, and/or biometric templates which are strings ofnumbers representing data that has been captured by a sensor andconverted to a string by a biometric recognition algorithm.

Decentralized Ledgers such as Blockchains, Tangles, HashGraphs etc.,referred to hereafter at Blockchains, can be used to create public orprivate records that provide an immutable transaction history. Theblocks may store various data, and in this embodiment, the blocks maystore biometric data in the form of an image or a biometric templatecreated from a biometric sensor (camera, fingerprint scanner, etc.)and/or from an algorithm analyzing an output from the biometric sensor(photograph, fingerprint scan, etc.). FIG. 19 shows a system ofbiometric authentication using a blockchain, according to an exemplaryembodiment.

In an exemplary biometric authentication method, a smart device 1912would run an application allowing a sensor 1916 or camera 1914 tocapture biometric data and optionally convert the biometric data to oneor more biometric templates. That biometric data and/or template(s)would be added to an encrypted block along with additional informationsuch as a device ID, a unique user ID, user identity information, thealgorithm/sensor version/type info, date and time stamp, GPSinformation, and/or other data.

The block may be added to the blockchain 1940 where it is stored. If theuser attempts to open the application again, or provides the public keyor a unique user identifier that corresponds to the public key for theblock into another application. Then the user is again presented withthe biometric data capture interface through which the user againpresents his/her biometric data to the sensor 1619 or camera 1914. Thecaptured biometric data may again optionally be converted to a biometrictemplate on the device 1912. Next, the user's previous block isrequested from the blockchain 1940 and is downloaded to the smart device1912 where a private key may be kept in the application to decrypt theblock. The data and/or biometric template(s) from the block can now becompared to the recently captured biometric data and/or biometrictemplate(s). If a match is found, then the user is authenticated andgranted access to the application, can make a transaction, etc. and thesuccessful decryption of the block and the matching of the templates canbe recorded with any combination of the data, the transaction, originaltemplate, the most recently successfully matched template or both may bestored in the new block.

In addition to or as an alternative to the comparison and matching beingdone on the device 1912, the comparison and matching may be completed onthe blockchain ledger servers 1940. In this instance, biometric dataobtained at the user device 1912 and/or biometric template(s) generatedat the user device 1912 from the biometric data is encrypted and sent tothe blockchain ledger servers 1940. Next, the public key and the privatedecryption key may be sent to the blockchain ledger servers 1940 todecrypt one or more previous blocks of the user's biometric informationand/or template(s) as well as to decrypt the most recently sentbiometric data and/or template(s). The blockchain ledger servers 1940then run the matching algorithms to determine if the biometricinformation and/or template(s) stored in the block and the most recentlycollected biometric information and/or template(s) are deemed a match bythe thresholds previously set in the matching algorithm. By providingtemplate matching on all the blockchain ledger severs 1940 (which couldbe hundreds or thousands of servers), an account provider can be surethat the device 1912 running the application has not been compromised ifthe matching results are the same as on the blockchain ledger servers1940. The device 1912 and all of the blockchain ledger servers 1940would have to be compromised at the same time for a hacker to change allof them, which of course would be highly unlikely if not impossible.

In yet another embodiment a dedicated “matching server” 1950 could beemployed that would be sent a copy of both the recently collectedbiometric information and/or template(s) from the device and thebiometric information and/or template(s) in the block. The device 1912may provide the decryption key directly to the matching server 1950, orthe blockchain 1940 could be instructed to send the encrypted biometrictemplate(s) to the matching server with a “smart contract” which is aset of computer instructions coded into the block. This is a feature ofblockchains with decentralized processing abilities like Ethereum.

It is also envisaged that when a new device requests a block using auser's unique ID, for example an email address, phone number, or apublic key, that the device is only authorized to download blocks in thechain that contain biometric templates of the user that are associatedwith that unique ID because the device contains the private keys. So theuser's most recent templates could be compared with all the templatesthat have been captured and are stored on the blockchain, allowing formultiple matches. This may provide fewer false rejections of the correctusers that can result from changes in appearance due to lighting, aging,makeup, hair, beard, glasses, etc.

In one configuration of the system and method disclosed herein, there isa private key and the private key will decrypt the block contents, butthe biometric data inside the block is what is used on the comparison todetermine if there is a match between new biometric data and storedbiometric data. Thus, the private key is required to gain access to thebiometric data block. The private key may be created by the user, thesystem, or the private key could corresponded to a combination of uniqueidentifiers that are is easier to remember, a phone number, a socialsecurity number, an email address and a date of birth, etc., and thusalso unique to the user. In this configuration, it's possible andcontemplated that there are two blockchains, one with the personal datain it, and one with anonymous storage of biometrics templates only, init. The personal data blocks in the first blockchain would be decryptedby a private key or corresponding personal data combos that only youknow, and you share it only with specific vendors that you want to beable to verify that identity, then in that data the block number ofanother block(s) with your biometric data is appended to that record andthen the app can go unlock that block and match/update your newlyuploaded biometric data to the data in that biometric block.

In addition to the biometric matching, the application collecting thebiometric data may perform liveness tests on the biometric datacollected, such as those described above. If the user is proven toexhibit traits that typically only exist in living humans, at the exactmoment that the identity is verified then the biometric data can betrusted to be from a real human being, not a non-living object such as aphoto or video spoof.

FIG. 20 is a schematic of a computing or mobile device, or server, suchas one of the devices described above, according to one exemplaryembodiment. FIG. 20 shows an example of a computing device 2070 and amobile computing device 2050, which may be used with the techniquesdescribed here. Computing device 2070 is intended to represent variousforms of digital computers, such as laptops, desktops, workstations,personal digital assistants, servers, blade servers, mainframes, andother appropriate computers. Computing device 2050 is intended torepresent various forms of mobile devices, such as personal digitalassistants, cellular telephones, smart phones, and other similarcomputing devices. The components shown here, their connections andrelationships, and their functions, are meant to be exemplary only, andare not meant to limit the implementations described and/or claimed inthis document.

Computing device 2070 includes a processor 2002, memory 2004, a storagedevice 2006, a high-speed interface or controller 2008 connecting tomemory 2004 and high-speed expansion ports 2010, and a low-speedinterface or controller 2012 connecting to low-speed bus 2014 andstorage device 2006. Each of the components 2002, 2004, 2006, 2008,2010, and 2012, are interconnected using various busses, and may bemounted on a common motherboard or in other manners as appropriate. Theprocessor 2002 can process instructions for execution within thecomputing device 2070, including instructions stored in the memory 2004or on the storage device 2006 to display graphical information for a GUIon an external input/output device, such as display 2016 coupled tohigh-speed controller 2008. In other implementations, multipleprocessors and/or multiple buses may be used, as appropriate, along withmultiple memories and types of memory. Also, multiple computing devices2070 may be connected, with each device providing portions of thenecessary operations (e.g., as a server bank, a group of blade servers,or a multi-processor system).

The memory 2004 stores information within the computing device 2070. Inone implementation, the memory 2004 is a volatile memory unit or units.In another implementation, the memory 2004 is a non-volatile memory unitor units. The memory 2004 may also be another form of computer-readablemedium, such as a magnetic or optical disk.

The storage device 2006 is capable of providing mass storage for thecomputing device 2070. In one implementation, the storage device 2006may be or contain a computer-readable medium, such as a hard diskdevice, an optical disk device, or a tape device, a flash memory orother similar solid-state memory device, or an array of devices,including devices in a storage area network or other configurations. Acomputer program product can be tangibly embodied in an informationcarrier. The computer program product may also contain instructionsthat, when executed, perform one or more methods, such as thosedescribed above. The information carrier is a computer- ormachine-readable medium, such as the memory 2004, the storage device2006, or memory on processor 2002.

The high-speed controller 2008 manages bandwidth-intensive operationsfor the computing device 2070, while the low-speed controller 2012manages lower bandwidth-intensive operations. Such allocation offunctions is exemplary only. In one implementation, the high-speedcontroller 2008 is coupled to memory 2004, display 2016 (e.g., through agraphics processor or accelerator), and to high-speed expansion ports2010, which may accept various expansion cards (not shown). In theimplementation, low-speed controller 2012 is coupled to storage device2006 and low-speed bus 2014. The low-speed bus 2014, which may includevarious communication ports (e.g., USB, Bluetooth, Ethernet, wirelessEthernet) may be coupled to one or more input/output devices, such as akeyboard, a pointing device, a scanner, or a networking device such as aswitch or router, e.g., through a network adapter.

The computing device 2070 may be implemented in a number of differentforms, as shown in the figure. For example, it may be implemented as astandard server 2020, or multiple times in a group of such servers. Itmay also be implemented as part of a rack server system 2024. Inaddition, it may be implemented in a personal computer such as a laptopcomputer 2022. Alternatively, components from computing device 2070 maybe combined with other components in a mobile device (not shown), suchas device 2050. Each of such devices may contain one or more ofcomputing device 2070, 2050, and an entire system may be made up ofmultiple computing devices 2070, 2050 communicating with each other.

Computing device 2050 includes a processor 2052, memory 2064, aninput/output device such as a display 2054, a communication interface2066, and a transceiver 2068, among other components. The device 2050may also be provided with a storage device, such as a microdrive orother device, to provide additional storage. Each of the components2050, 2052, 2064, 2054, 2066, and 2068, are interconnected using variousbuses, and several of the components may be mounted on a commonmotherboard or in other manners as appropriate.

The processor 2052 can execute instructions within the computing device2050, including instructions stored in the memory 2064. The processormay be implemented as a chipset of chips that include separate andmultiple analog and digital processors. The processor may provide, forexample, for coordination of the other components of the device 2050,such as control of user interfaces, applications run by device 2050, andwireless communication by device 2050.

Processor 2052 may communicate with a user through control interface2058 and display interface 2056 coupled to a display 2054. The display2054 may be, for example, a TFT LCD (Thin-Film-Transistor Liquid CrystalDisplay) or an OLED (Organic Light Emitting Diode) display, or otherappropriate display technology. The display interface 2056 may compriseappropriate circuitry for driving the display 2054 to present graphicaland other information to a user. The control interface 2058 may receivecommands from a user and convert them for submission to the processor2052. In addition, an external interface 2062 may be provide incommunication with processor 2052, so as to enable near areacommunication of device 2050 with other devices. External interface 2062may provide, for example, for wired communication in someimplementations, or for wireless communication in other implementations,and multiple interfaces may also be used.

The memory 2064 stores information within the computing device 2050. Thememory 2064 can be implemented as one or more of a computer-readablemedium or media, a volatile memory unit or units, or a non-volatilememory unit or units. Expansion memory 2074 may also be provided andconnected to device 2050 through expansion interface 2072, which mayinclude, for example, a SIMM (Single In Line Memory Module) cardinterface. Such expansion memory 2074 may provide extra storage spacefor device 2050, or may also store applications or other information fordevice 2050. Specifically, expansion memory 2074 may includeinstructions to carry out or supplement the processes described above,and may include secure information also. Thus, for example, expansionmemory 2074 may be provide as a security module for device 2050, and maybe programmed with instructions that permit secure use of device 2050.In addition, secure applications may be provided via the SIMM cards,along with additional information, such as placing identifyinginformation on the SIMM card in a non-hackable manner.

The memory may include, for example, flash memory and/or NVRAM memory,as discussed below. In one implementation, a computer program product istangibly embodied in an information carrier. The computer programproduct contains instructions that, when executed, perform one or moremethods, such as those described above. The information carrier is acomputer- or machine-readable medium, such as the memory 2064, expansionmemory 2074, or memory on processor 2052, that may be received, forexample, over transceiver 2068 or external interface 2062.

Device 2050 may communicate wirelessly through communication interface2066, which may include digital signal processing circuitry wherenecessary. Communication interface 2066 may provide for communicationsunder various modes or protocols, such as GSM voice calls, SMS, EMS, orMMS messaging, CDMA, TDMA, PDC, WCDMA, CDMA2000, or GPRS, among others.Such communication may occur, for example, through radio-frequencytransceiver 2068. In addition, short-range communication may occur, suchas using a Bluetooth, Wifi, or other such transceiver (not shown). Inaddition, GPS (Global Positioning system) receiver module 2070 mayprovide additional navigation- and location-related wireless data todevice 2050, which may be used as appropriate by applications running ondevice 2050.

Device 2050 may also communicate audibly using audio codec 2060, whichmay receive spoken information from a user and convert it to usabledigital information. Audio codec 2060 may likewise generate audiblesound for a user, such as through a speaker, e.g., in a handset ofdevice 2050. Such sound may include sound from voice telephone calls,may include recorded sound (e.g., voice messages, music files, etc.) andmay also include sound generated by applications operating on device2050.

The computing device 2050 may be implemented in a number of differentforms, as shown in the figure. For example, it may be implemented as acellular telephone 2080. It may also be implemented as part of a smartphone 2082, personal digital assistant, a computer tablet, or othersimilar mobile device.

Thus, various implementations of the systems and techniques describedhere can be realized in digital electronic circuitry, integratedcircuitry, specially designed ASICs (application specific integratedcircuits), computer hardware, firmware, software, and/or combinationsthereof. These various implementations can include implementation in oneor more computer programs that are executable and/or interpretable on aprogrammable system including at least one programmable processor, whichmay be special or general purpose, coupled to receive data andinstructions from, and to transmit data and instructions to, a storagesystem, at least one input device, and at least one output device.

These computer programs (also known as programs, software, softwareapplications or code) include machine instructions for a programmableprocessor, and can be implemented in a high-level procedural and/orobject-oriented programming language, and/or in assembly/machinelanguage. As used herein, the terms “machine-readable medium”“computer-readable medium” refers to any computer program product,apparatus and/or device (e.g., magnetic discs, optical disks, memory,Programmable Logic Devices (PLDs)) used to provide machine instructionsand/or data to a programmable processor, including a machine-readablemedium that receives machine instructions as a machine-readable signal.The term “machine-readable signal” refers to any signal used to providemachine instructions and/or data to a programmable processor.

To provide for interaction with a user, the systems and techniquesdescribed here can be implemented on a computer having a display device(e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor)for displaying information to the user and a keyboard and a pointingdevice (e.g., a mouse or a trackball) by which the user can provideinput to the computer. Other kinds of devices can be used to provide forinteraction with a user as well; for example, feedback provided to theuser can be any form of sensory feedback (e.g., visual feedback,auditory feedback, or tactile feedback); and input from the user can bereceived in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in acomputing system (e.g., computing device 2070 and/or 2050) that includesa back end component (e.g., as a data server), or that includes amiddleware component (e.g., an application server), or that includes afront end component (e.g., a client computer having a graphical userinterface or a Web browser through which a user can interact with animplementation of the systems and techniques described here), or anycombination of such back end, middleware, or front end components. Thecomponents of the system can be interconnected by any form or medium ofdigital data communication (e.g., a communication network). Examples ofcommunication networks include a local area network (“LAN”), a wide areanetwork (“WAN”), and the Internet.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

Biometric data templates are not suitable to be used as public keys, andcannot be reliably hashed into public keys because each session containsbiometric data that is slightly different than previous sessions.Biometric matching is done by creating a probability of a match andsetting an acceptable threshold. In one embodiment, the settings aresuch that if the comparison reveals collected biometrics data that a100% match, it is may be considered to not be a match an instead apotential fraud attempt because biometric data comparisons are typicallynever a 100% a match unless a replay (of the same data) attack is beingperpetrated. Because biometrics rely on probability to confirm amatching identity it is important not to allow bad actors tospecifically target a known identity armed with copies of thatindividual's biometric data, such a photos, videos or masks. This may beachieved by limiting access to the blockchain using user question data.It is also contemplated that an efficient means to provide a blockchainwherein the identity of the individual whose biometric data contained ineach encrypted block is not readily known to the other users of theblockchain and therefore cannot be easily singled out and targeted isdesirable. This is typically accomplished in blockchains with a PublicKey, however if a bad actor knows the public key for a specificindividual they can target a spoofing attack with reproduction of thatindividual's biometric data. By using a questions layer (requiring usersto answer questions before granting access to the block chain) that doesnot require the users to store, transmit or even know their public key,the likelihood that a bad actor could match a specific block to aspecific user and then spoof the system is reduced significantly. Thismethod would allow a user to easily input data from memory that wouldthen be used to recreate their Public Key and then used to identify tothe blocks in the block chain system that contain their encryptedbiometric data for authentication but not use personally identifiableinformation (PII) to do so. In one embodiment, this is accomplishedthrough a series of questions that the person answers to generate userquestion data. In one embodiment, these questions are such that theperson would always know the answers, such as city of birth, parentnames, or high school name. In one embodiment, the questions are suchthat the person creates the answers such as favorites, things thatchange, or opinion based questions. Examples of this type of userquestion data include favorite color, favorite food, or favoriteholiday. In one embodiment, the user question data is created based onsystem requirements but does not relate to the user. Examples of thistype of user data may be data containing only numbers, data containingspecial symbols, data containing only letters, and/or data containing arequired number of each type of characters. Some of this data may beeasily recalled and thus not forgotten by the user. Other data is lesslikely to be guessed by others, but is harder to remember. It iscontemplated that any other type of information and questions may beused for the user questions and associated user question data.

For the questions that are easily recalled or which are memorized, thisuser question data is always available to the user. In one embodiment,as part of an identification process, the user is asked questions orasked to provide the answers (user question data) to the questions. Theuser question data is concatenated and then hashed to create a publickey and/or block identifier. This may then be used for one or more ofthe following: identify the user, identify the block associated with theuser in the block chain, combined with personally identifiableinformation to identify the user or the blocks that contain a user'sencrypted information. For example, this concatenated and hashed userquestion data may identify to the authentication system which block tomatch their biometric authentication session against. This user questiondata may be referred to as a public key.

Examples of the type of user questions include, but are not limited to,best year of your life, number of siblings, shoe size, height, favoritecolor, eye color, last 4 digits of your first phone number, middle name,parents name, favorite grade in school, favorite month, favorite day ofthe year, best physical trait, school name, favorite food, dietarychoices, political affiliation, and religious affiliation or any othersimilar type of question or data. In one embodiment the data is wellknown (and not forgettable by the user) but is not of the type that isof public record or can be obtained by typical identity theft methods.

In one example method of operation, this authentication system may beused when obtaining a money loan, at an automobile dealership, or anyother situation where it is necessary or desired to positively identifythe person and allow them to grant access their credit bureauinformation to a third party (or some other function where identity isrequired and important).

FIG. 21 illustrates a block diagram of an example system and environmentof use. In reference to FIG. 21, at the automobile dealer (business)2124 (one example environment of use), the user is presented with acomputer interface 2104, such as a tablet. Using the computer interface2104, the user questions data may be inputted into a secure applicationor web interface with drop down fields or text fields which do not storeor record the user's input. The user is presented with questions forwhich they select their previously specified answers, or they providethe user question data without being presented with questions. At thisstage a hash operation or other algorithm processing may occur to theone or more user question data. The hash may occur on device 2104 or ona separate device 2108. Example operations that may occur on the userquestion data may include, but is not limited to hash, encryption,combination with personal identifiable information such as name orsocial security number. By hashing or otherwise processing the userquestion data at this stage (prior to electronic transmission orstorage) the user question data is protected. A biometric authenticationsession may also be performed on the same device prior to, at the sametime as, or after, providing and processing the user question data.

The user device 2104 provides the user question data which, afterhashing or other processing is provided 2150 by electronic transmission,to the remote authentication system 2018 with associated database 2112to identify both the user and their block. The authentication system2108 can run a same hash operation on the stored previously captureddata, stored on data base 2112 to determine if the received data matchesa user, account, block in a blockchain, or another identifier. Inaccordance with blockchain operation, many authentication systems 2018may be provided at different locations, or there blockchain data for theuser maybe stored in many different databases 2112 at differentlocations. The authentication system 2108 may provide communication backto the user. Thus, the submitted user answer data matching the storeduser answer data may identify the blockchain which stores the user'sauthentication data, grant access to the blockchain, or both.

Once the block or blocks that are associated with that public key areidentified, it can be decrypted with the hash to obtain the contents ofthat block. In this example, the hashed user question data providesaccess to the user's blocks and can be used to reveal the biometric datastored in the block, which is then compared to the newly submitteduser's authentication attempt (facial data and movement data) todetermine if the user's identity matches the identity stored in theblock chain (distributed at different locations thus preventingunauthorized access and unauthorized changes). If a match occurs, then,credit agency, loan department or other entity 2116 will receive noticeof the authentication via communication 2160. This in turn may allow theloan to occur or a credit report to be sent to the business 2124 viacommunication 2170. For example, if the loan or credit is approved bythe 3^(rd) party 2116, then that will be communicated to the cardealership 2124 which in turn will allow the car to be driven away withonly the down payment and/or a payment agreement. The match may also bea gateway requirement before the dealership can pull a user's credit oraccess a user's credit report. It is contemplated that in someembodiments the lender 2116 and business 2124 may be combined.

Using this method, the user may provide user question data that wouldnot be easily known by a third party since it is personal to the userand not asked by third parties. This form of data and associated methodovercomes the drawbacks of the prior art by providing and associatingcomplex data (user question data) that the user will have memorized andthus always with them but yet that others don't know, and which uniquelyidentifies themselves or their block or account in the blockchain. Theanswer to the user question data is complex, difficult to guess andlonger and more difficult to obtain by a third party than the nine digitsocial security number or other personal information (PII) but isgenerally easy for the user to remember.

If a third party knows the answers to all of the user's questions, thesystem would only allow them to attempt to match presented biometricdata with the data stored in the blocks for that user. Because the thirdparty will not easily match the biometric data with a photo, video ormask if the biometric authentication has strong depth and livenessdetection systems, the authentication attempt would be not authenticatedand thus the third party would not able to impersonate the user. Inaddition an email address or mobile phone number could be entered intoto the encrypted block when the user is enrolling and an email or textmessage could be sent to the registered user's email address or phonenumber every time that block is unlocked and the biometric data matchedfrom an authentication session or for every attempt. This would alert auser if a bad actor had gained the answers to their public keygenerating questions and was attempting to impersonate them throughvarious means such by using a look-alike of the user for a biometricspoof. If the bad actor was successful in spoofing the system the realregistered user would get an email saying that a successfulauthentication session had been performed and if it was not them theycould initiate steps to stop the bad actor. Notification could also beprovided for unsuccessful attempts to access the block. It iscontemplated that notification may be sent by email, phone call, ortext, or any combination. In embodiment, the system may alternatively orin addition send a verification code to the user, such as by mail, phone(voice), or text, that must be entered with the user question data toprovide an additional level of security. Sending and entry ofverification codes are known and thus not described in detail.

It is contemplated that the user question data can arrive into thedealership, credit agency, bank or other entity, in any manner. Forexample, the user question data may be entered by the user with thebusiness's device, uploaded by the user on their own device, by using athird party kiosk, provided by telephone, text messages, or any othermeans. Using this innovation, a method of creating a public key thatpeople can easily remember because it is well suited for how humanmemory works. While the user question data may not all be secret, it canbe easily remembered and it is not publicly available and has not beenpart of the numerous data breaches, as the questions are not typicaldata such as social security number, birth date, and middle name. Anynumber of questions may be provided to create the public key, such asfor example, two questions or ten questions such that the morequestions, the less likely someone will know or guess the answers toaccess the block data for an authentication attempt. While it ispossible to use a user's name, social security number, email or phone,this data would also identity the user and easily lead back to theblocks in the blockchain but would expose the user's identity and canbecome known due to use of that information in other situations. Withthe disclosed system, utilizing user question data, the identity of theuser and the block that stores their corresponding biometric data areanonymous to everyone including the operators of the blockchain nodes.It is still possible for an individual to provide all of the answers totheir user questions to a dishonest 3^(rd) party or have thatinformation phished from them unknowingly, but this is unlikely. Forthis to occur would still require the bad actor to spoof the biometricauthentication system to gain access to any credit information or otherinformation, which due to the extreme accuracy of the authenticationroutines disclosed herein, is extremely unlikely.

FIG. 22 illustrates as flow chart providing an example method ofoperation. This is but one possible method of operation and it iscontemplated that in other systems and environments the method maydepart from that disclosed in FIG. 22 without departing from the claims.At a step 2204 the user, business, or system initiates an authenticationsession and as part of this, at a step 2208 the business attempting toverify the identity of the person may present to the user a computingdevice for data entry. The device may be any computer, including atablet. The device and any server described herein may include aprocessor with memory such that the memory stored non-transitory machineexecutable instructions which are executable on the processor. Thenon-transitory machine executable instructions may also be referred toas software. At a step 2212 the computing device presents questions tothe user and as the user provides their answers the computing deviceaccepts the user question data at step 2216.

At a step 2020 the system processes the user question data to generatehashed user question data. This could also occur at a remote location.The hashed user question data may serve as a public key. Then, at a step2024 the system uploads the hashed user question data to a remote server(encryption optional). Then, at a step 2228, the system, such as aremote computer configured for user authentication, compares hashed userquestion data from the user to stored hashed user question data that isstored on one or more databases. The stored data was from earlier inputfrom the user when the identity was known.

At a step 2232, responsive to a match between the stored user questiondata and the submitted user question data (hashed or unhashed), thesystem identifies the user's blockchain. Thereafter, the system requestsan authentication attempt from the user to collect facial data andmovement data during authentication. This occurs at a step 2236. In thisembodiment, this data is collected the user question data matches, butin other embodiments, the user facial and movement data may be collectedat the time of collection of the user question data. At a step 2240, thesystem uploads the authentication data to a remote server from a user(encryption optional) and at a step 2244 the system uses the hashed userquestion data as a public key to unlock the authentication data (facial,movement, or combination thereof) that is stored in the blockchain. Thismay occur at multiple locations such is the nature of a distributedblockchain.

At a step 2248 the authentication system compares the stored userauthentication data to the user submitted authentication data todetermine if there is a match within a predetermine threshold. Asdiscussed above, 100% matches are unlikely or impossible so thesimilarities between data should be within some range or threshold whichcan be adjusted based on the use and need to verify identity. At a step2252, responsive to a match, access is allowed or the requestedinformation is provided such as access to a credit score, credit report,or authorization for other type transaction or loan. This system can beused in any scenario where verifying a person's identity is important.For example, buying a expensive watch or jewelry would benefit fromidentify verification, or access to a secure location or data.

While various embodiments of the invention have been described, it willbe apparent to those of ordinary skill in the art that many moreembodiments and implementations are possible that are within the scopeof this invention. In addition, the various features, elements, andembodiments described herein may be claimed or combined in anycombination or arrangement.

What is claimed is:
 1. A method for authenticating identity of acustomer as part of a business transaction comprising: presenting acustomer, with customer questions, the customer questions havingcorresponding customer answers; receiving customer answers from thecustomer in response to the presenting of customer questions; processingthe customer answers to create processed customer answers; transmittingthe processed customer answers to a remote computing device; comparingprocessed customer answers to stored data at the remote computingdevice; responsive to the comparing determining that a match has notoccurred, then denying further authentication; responsive to thecomparing determine that a match has occurred, then allowing furtherauthentication by capturing and processing one or more facial images ofthe customer to verify the identity of the customer and liveness of thecustomer.
 2. The method of claim 1 wherein the processed customeranswers are encrypted, subject to a hash operation, or both.
 3. Themethod of claim 1 further comprising: converting the one or more facialimages to captured authentication data; and comparing the capturedauthentication data to stored authentication data to determining if amatch occurs.
 4. The method of claim 3 wherein the stored authenticationdata is stored in a blockchain and the comparing, for a match, thereverse processed customer answers to stored customer answers datacontrols access to the blockchain storing the stored authenticationdata.
 5. The method of claim 1 wherein a result of the identity andliveness verification of the customer is communicated to a business tothereby verify the identity of the customer to the business.
 6. Themethod of claim 5 wherein the business is a credit reporting agency or alender.
 7. The method of claim 1 wherein authentication furthercomprises: verifying the liveness of the customer by processing a firstimage of the customer's face captured at a first distance from thecustomer and capturing a second image of the customer's face captured ata second distance from the customer.
 8. The method of claim 7 whereinthe authentication further comprises comparing at least one image of thecustomer's face to a previously captured image of the customer's facewhich is part of stored authentication data.
 9. An authentication systemto verify a user's identity comprising: a data collection device havinga processor and memory storing non-transitory machine executable codewhich is executable by the processor, the machine executable code of thedata collection device configured to: present user related questions tothe user; receive answers to the user related questions, the answersentered by the user into the data collection device; process the answersto create secured answer data; transmit the secured answer data;responsive to instructions from a remote server, collect and transmitcollected authentication data from the user; the remote server having aprocessor and memory storing non-transitory machine executable codewhich is executable by the processor, the machine executable codeconfigured to: receive the secured answer data from the data collectiondevice and: process the secured answer to determine if the receivedsecured answer data matches stored secured answer data; responsive tothe received secured answer data not matching the stored secured answerdata, denying access to stored authentication data for the user;responsive to the received secured answer data matching the storedsecured answer data: initiate an authentication session by communicatingwith the data collection device to collect and transmit collectedauthentication data; receive collected authentication data from the datacollection device; and compare the collected authentication datareceived from the data collection device to stored user authenticationdata stored on the remote server to determine if a match occurs, suchthat a match verifies the identity of the user.
 10. The system of claim9 wherein the secured answer data comprises encrypted answers or hashedanswers.
 11. The system of claim 9 wherein the collected authenticationdata comprises one or more images of the user captured by a camera ofthe data collection device.
 12. The system of claim 11 wherein the userauthentication data comprises a first image of the user's face captured,by the camera, at a first distance separating the user and the cameraand second image of the user's face captured, by the camera, at a seconddistance separating the user and the camera, such that the firstdistance is different from the second distance.
 13. The system of claim9 further comprising transmitting a verified identity notice to a thirdparty server and responsive thereto, receiving data from the third partyserver as part of a business transaction.
 14. The system of claim 9wherein the stored user authentication data is stored in a blockchainand the blockchain storing the stored user authentication data is onlyaccessed when the received secured answer data matches the storedsecured answer data.
 15. An authentication system for use by a businessto verify identity of a user, the authentication system comprising: adata collection device having a screen and a user interface, the datacollection device configured to: receive answers from the user toquestions presented to the user; process the answers to create secureanswer data; transmit the secure answer data to a verification server; averification server configured to: receive the secure answer data fromthe data collection device; compare the secure answer data or processedsecure answer data to stored answer data; responsive to the comparingdetermining that the secure answer data or processed secure answer datadoes not match the stored answer data, terminating the identifyverification; responsive to the comparing determining the secure answerdata or processed secure answer data matchings the stored answer data,initiating an authentication session which includes capture of one ormore images of the customer's face with a camera associated with thedata collection device or another device.
 16. The system of claim 15wherein the data collection device is an electronic device owned by theuser.
 17. The system of claim 15 wherein the data collection device isan electronic device owned by the business.
 18. The system of claim 15wherein the stored answer data is created by performing the sameprocessing on the answers as occurred by the data collection device toform the secure answer data.
 19. The system of claim 15 wherein thequestions presented to the user are based on information personal to theuser.
 20. The system of claim 15 wherein initiating an authenticationsession comprises: providing notice, from the verification server, toinitiate the authentication session by sending a message from theverification server to the data collection device or the another device;capturing at least one image of the user with a camera associated withthe data collection device or the another device; processing the atleast one image to generate captured image data; transmitting thecaptured image data to the verification server; at the verificationserver, processing the captured image data to verify threedimensionality of the user; comparing the captured image data to storedimage data derived from at least one previously captured image of theuser to determine if match occurs within a threshold range; andresponsive to verifying three dimensionality of the user and obtainingthe match within the threshold range, then verifying the identity of theuser to the business.
 21. The system of claim 15 wherein biometricinformation is stored in a blockchain.
 22. The system of claim 15wherein the one or more images of the user's face comprises a firstimage captured with the camera at a first distance from the user and asecond image captured with the camera at a second distance from theuser, the first distance different than the second distance.
 23. Amethod for verifying identity of a customer by a business comprising:initiating an identity verification session for the customer; at thebusiness, presenting to questions to the customer, the questions havingstored answers which are stored at a remote location; at the business,receiving customer answers to the questions; transmitting the customeranswers or a processed version of the customer answers to anauthentication system; receiving the customer answers or the processedversion of the customer answers at the authentication system; comparingthe customer answers or the processed version of the customer answers tostored customer answers or a stored processed version of the customeranswers to determine if a match occurs; if a match does not occur,providing notice to the business of a failure to match and ending theidentity verification processes; if a match does occur, initiating anauthentication process by obtaining one or more images of the customer'sface with a camera; processing one or more of the images of thecustomer's face to generate captured facial image data; transmitting thecaptured facial image data to the authentication system; processing thecaptured facial image data to determine three-dimensionality andliveness of the customer generating the captured facial image data;comparing the captured facial image data to stored facial image dataconfirm the stored facial image data matches the captured facial imagedata, the stored facial image data based on previously captured imagesof the customer's face.
 24. The method of claim 23 further comprising,responsive to the stored facial image data matching the captured facialimage data, sending an identity verification success message to thebusiness.
 25. The method of claim 23 further comprising, responsive tothe stored facial image data matching the captured facial image data,sending an identity verification success message to a credit reportingagency so the credit reporting agency can sent a credit report to thebusiness.
 26. The method of claim 23 further comprising, responsive tothe stored facial image data matching the captured facial image data,sending an identity verification success message to a lender so thelender will provide a loan or financing to the customer.
 27. The methodof claim 23 wherein the one or more images of the user comprise a firstimage capture with the camera a first distance from the customer's faceand a second image captured with the camera a second distance from theuser's face, the first distance different than the second distance. 28.The method of claim 23 wherein the customer answers are encrypted orhashed prior to transmitting to the authentication system.
 29. Themethod of claim 23 wherein comparing the customer answers or theprocessed version of the customer answers to stored customer answers ora stored processed version of the customer answers controls access toauthentication data stored is a blockchain.